In today’s financial landscape, personalization is no longer a luxury; it’s a customer expectation. Yet, according to Adobe’s latest State of Customer Experience in Financial Services in an AI-Driven World report, only 36% of the customer journey is currently personalized, despite 74% of financial services executives acknowledging that their customers expect tailored interactions.

This gap isn’t just a missed opportunity; it’s a trust breaker.

Why Personalization Matters More Than Ever

Financial decisions are deeply personal. Whether a customer is exploring mortgage options, planning for retirement, or managing small business finances, they expect advice and experiences that reflect their unique goals and life stage. Generic nudges and one-size-fits-all messaging simply don’t cut it anymore.

Early-stage interactions—like product discovery or financial education—are especially critical. These are high-value moments where relevance builds trust and guides decision-making. Yet many institutions fall short, lacking the orchestration needed to deliver personalized engagement across these initial touchpoints.

What’s Holding Institutions Back?

The report highlights several barriers:

• Fragmented data systems that prevent a unified view of the customer
• Legacy operating models that prioritize product silos over customer journeys
• Compliance concerns that limit personalization efforts, even when customers expect it

These challenges are compounded by the rise of AI-powered experiences, which demand real-time, context-aware personalization across channels.

The Path Forward: Adaptive, Lifecycle Personalization

To close the gap, financial institutions must evolve from episodic personalization to adaptive, full-lifecycle engagement. That means:

• Investing in unified customer profiles and behavioral insights
• Building real-time content engines that respond to customer signals
• Designing personalization strategies that grow with the relationship and not just the transaction

Download the full Adobe report to explore the top 10 insights shaping the future of financial services, and discover how your organization can lead with intelligence, responsibility, and trust.

Learn About Perficient and Adobe’s Partnership

Are you looking for a partner to help you transform and modernize your technology strategy? Perficient and Adobe bring together deep industry expertise and powerful experience technologies to help financial services organizations unify data, orchestrate journeys, and deliver customer-centric experiences that build trust and drive growth.

Get in Touch With Our Experts

Acquia is known for its open-source roots and marketer-friendly tools, and its approach to AI reflects that ethos. As digital experience platforms evolve, Acquia is embedding agentic and Generative AI to make experience creation more accessible, intuitive, and scalable, especially for teams without deep technical resources. 

Forrester’s report, The Impact of AI on Digital Experience Platforms, discusses how vendors like Acquia are using AI to simplify workflows, automate content generation, and empower practitioners across roles — and Acquia’s recent innovations reflect its commitment to democratizing digital experience delivery. 

Supporting Marketers Behind the Scenes With Agentic AI

Launched earlier this year, Acquia Source allows marketers to build web pages using AI prompts that generate code behind the scenes and eliminate the need for developer intervention. These agentic capabilities are designed to reduce friction and accelerate time to market for digital experiences. 

Perficient DXP Practice Director Josh Hover and his team have been helping clients take advantage of these capabilities to streamline experience creation.  

Josh said, “Acquia’s agentic AI tools are helping marketers take control of experience creation. We’re working with clients to integrate these capabilities into their workflows so they can move faster without sacrificing quality.” 

Simplifying Experience Creation with GenAI

Acquia has been embedding GenAI into its platform for years. For example, it partnered with Clarifai to provide image auto-tagging. Today, however, GenAI is powering more advanced use cases. From generating page layouts to summarizing customer interactions, teams can deliver relevant experiences with less manual effort. 

Reflecting on these innovations, Josh notes how GenAI is helping teams scale without adding complexity.  

“Acquia’s GenAI features are especially valuable for teams with limited resources. We’re helping clients use these tools to scale content and streamline operations without being complicated,” he said.  

Perficient Named 2025 Gold Globe® Winner for Best Artificial Intelligence Service Provider | Learn More 

Enabling Responsible AI Adoption Across Teams

Successful AI adoption requires strong data foundations, human oversight, and change management. Acquia’s focus on accessibility makes these considerations even more critical. That’s why we partner with clients to ensure AI tools are deployed responsibly and aligned with business goals. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Acquia. Whether it’s orchestrating personalized journeys or deploying intelligent agents, we’re helping brands embrace AI responsibly and effectively. 

If you’re exploring how to bring AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Acquia expertise here.  

Contact us to learn more. 

As customer expectations continue to rise, financial services organizations are under increasing pressure to deliver personalized, seamless, and secure digital experiences. Adobe’s latest report, The Total Economic Impact of Adobe’s Content Supply Chain Solution, reveals how Generative AI and connected data are reshaping the industry and why now is the time for financial institutions to evolve.

A Wake-Up Call for Financial Services

Consumers today expect more than just secure transactions. They want personalized recommendations, consistent omnichannel experiences, and transparency in how their data and AI-generated content are used. Yet, Adobe’s research shows a significant gap between these expectations and what financial services brands currently deliver:

• 90% of consumers rate data privacy as critical, but only 58% feel their data is handled securely
• 79% expect consistent experiences across channels, but just 47% say brands deliver
• Only 33% feel brands anticipate their needs with relevant offers, despite 70% expecting it

This disconnect presents a clear opportunity for financial institutions to differentiate themselves by investing in AI-powered personalization and content delivery.

GenAI Moves From Concept to Competitive Advantage

Generative AI is no longer a futuristic concept; it is now a reality. It’s a strategic imperative. In 2025, 56% of financial services organizations are prioritizing GenAI to improve client interactions and employee productivity. Wealth and asset management firms lead the charge with 60% focusing on AI-driven client engagement compared to 52% in retail banking.

Use cases are expanding rapidly:

• Chatbots are the most mature application, with 49% of organizations already using them
• Journey optimization and data analysis are gaining traction, with over 40% of firms piloting or deploying solutions
• AI is also being used to automate workflows, generate creative content, and personalize customer experiences across channels

Efficiency, Engagement, and Growth

Executives are already seeing tangible benefits from AI adoption:

• 51% report major gains in content production speed
• 50% see improved team productivity
• 47% note freed-up resources for strategic initiatives

These improvements are driving better customer engagement and laying the foundation for scalable, personalized marketing.

Overcoming Compliance, Data Silos, and Culture

Despite the momentum, scaling AI in financial services isn’t without challenges. Governance, compliance, and privacy concerns top the list, especially in retail banking, where 59% of executives cite compliance as the biggest hurdle. Siloed data is another major issue, particularly in wealth and asset management, where 51% struggle to unify customer insights.

To move forward, organizations must:

• Establish cross-functional AI governance committees
• Invest in real-time data platforms
• Prioritize ethical AI practices to protect brand reputation

The Road Ahead

The Adobe report paints a clear picture: financial services organizations must embrace AI and digital transformation to stay competitive. Key trends shaping the future include:

• Hyper-Personalization | Real-time, one-to-one interactions are the goal, but only 33% of firms can update offers based on browsing history.
• Omnichannel Consistency | Practitioners feel pressure to deliver more content across more channels, with 43% citing increased volume demands.
• Sustainable Innovation | Wealth managers are leading the way in sustainable investing, responding to growing consumer demand.

To succeed, financial institutions must take a methodical, compliant approach to AI adoption, balancing innovation with trust. The winners will be those who connect data, content, and customer insights to deliver meaningful, personalized experiences at scale.

Ready to Transform Your Digital Experience Strategy?

Navigating the complexities of AI adoption, data governance, and digital transformation requires more than just technology. It demands deep industry expertise and a strategic partner who understands the nuances of financial services.

Our experts bring together Adobe solutions, generative AI innovation, and financial services experience to help you:

• Deliver personalized, compliant, and scalable digital experiences
• Break down data silos and activate real-time insights
• Accelerate content creation and journey optimization with AI
• Build trust through secure, transparent, and consistent customer interactions

Whether you’re modernizing for next-gen customers, launching new digital offerings, or scaling AI across your organization, we’re here to help you move forward with confidence.

Let’s connect and explore how we can elevate your customer experience together.

Optimizely has always been synonymous with experimentation. Its platform empowers organizations to test, learn, and optimize digital experiences with precision. Now, with the integration of agentic and generative AI, Optimizely is taking that mission further — helping teams not only run smarter experiments but also act on insights faster and more confidently. 

Forrester’s report, The Impact of AI on Digital Experience Platforms, discusses how vendors like Optimizely are embedding AI to support content creation, campaign testing, and practitioner enablement. Optimizely’s approach stands out for its focus on agility and continuous improvement. 

Agentic AI Turns Data Into Decisions

Optimizely’s Opal provides a unified view of customer interactions, enabling marketers to make informed decisions based on real-time data. Agentic AI capabilities are layered into this experience, offering recommendations, automating workflows, and guiding practitioners through complex optimization paths. 

Perficient Optimizely Director David Lewis explains how Perficient is helping clients unlock the full potential of these tools.  

Lewis said, “We’re seeing Optimizely’s AI capabilities accelerate how teams work—whether it’s Opal generating brand-consistent content in CMP, summarizing experiment results in Web Experimentation, or surfacing personalization ideas directly in Feature Experimentation. The real advantage is that these tools are connected to the workflows practitioners already use every day, so optimization happens naturally and at scale.” 

Accelerating Content and Campaign Innovation With GenAI

Optimizely’s GenAI features are designed to support rapid iteration. From generating brand-consistent content to summarizing customer behavior and simulating campaign outcomes, GenAI is helping teams move faster without compromising quality. 

Lewis shares how Perficient is guiding clients through this transformation. 

“We’re seeing GenAI help Optimizely users move faster, whether it’s writing audience-specific content or simulating campaign outcomes. The key is integrating these tools into workflows that already drive business value,” he said.  

Perficient Named 2025 Gold Globee® Winner for Best Artificial Intelligence Service Provider | Learn More 

Building a Smarter, Safer AI Strategy

Successful AI adoption requires strong data foundations, human oversight, and change management. That’s why we work with clients to ensure these elements are in place, especially when integrating AI into experimentation and optimization workflows. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Optimizely. Whether it’s orchestrating personalized journeys or deploying intelligent agents, we’re helping brands embrace AI responsibly and effectively. 

If you’re exploring how to bring Optimizely’s AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Optimizely expertise here.  

Contact us to learn more.

Sitecore has long positioned itself as a leader in composable digital experience platforms, offering flexibility and scalability for organizations looking to tailor their tech stacks. As AI becomes a central force in experience delivery, Sitecore is embedding agentic and Generative AI capabilities to help brands personalize at scale, streamline operations, and empower practitioners. 

Forrester’s report, The Impact of AI on Digital Experience Platforms, discusses how vendors like Sitecore are evolving their platforms to support intelligent orchestration and content creation. Sitecore’s modular architecture makes it uniquely suited to adopt these innovations. 

Empowering Practitioners With Agentic AI

Sitecore’s copilot launched in late 2024 and is designed to help marketers build hyper-personalized campaigns with less manual effort. These intelligent agents assist with segmentation, content recommendations, and campaign optimization all while integrating seamlessly into Sitecore’s composable stack. 

Perficient Sitecore Consulting Principal Mark Ursino has seen growing interest in Sitecore’s agentic AI capabilities, especially among clients looking to unify customer data and reduce friction in campaign execution. 

Ursino said, ” Sitecore’s AI orchestration capability, Stream, launched in late 2024 and is helping marketers move faster and smarter. We’re working with clients to integrate these tools into their workflows so they can focus on strategy while AI handles the complexity.” 

GenAI in a Composable World

Sitecore’s GenAI features are designed to complement its modular approach. Whether generating brand-consistent content, summarizing customer interactions, or supporting A/B testing, GenAI is helping teams deliver more relevant experiences without overhauling their existing infrastructure. 

“Sitecore’s composable architecture makes it easier to plug in GenAI capabilities where they’ll have the most impact. We’re helping clients identify those opportunities and align them with measurable goals,” said Ursino.  

Perficient Named 2025 Gold Globee® Winner for Best Artificial Intelligence Service Provider | Learn More 

Building a Responsible AI Foundation

Successful AI adoption requires more than just new features. Organizations must invest in strong data foundations, human oversight, and change management. That’s why we partner with clients to ensure these pillars are in place, especially when integrating AI into modular environments like Sitecore. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Sitecore. Whether it’s orchestrating personalized journeys or deploying intelligent agents, we’re helping brands embrace AI responsibly and effectively. 

If you’re exploring how to bring AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Sitecore expertise here.  

Contact us to learn more. 

Salesforce continues to evolve its digital experience capabilities by embedding artificial intelligence across its platform. Forrester’s report, The Impact of AI on Digital Experience Platforms, discusses how vendors like Salesforce are integrating agentic AI and Generative AI (GenAI) to streamline experience operations and empower practitioners. 

With tools like  Agentforce, Salesforce is moving beyond traditional automation to deliver intelligent, connected experiences. These innovations are designed not only to enhance customer engagement but also to support the practitioners behind the scenes — enabling smarter orchestration, faster decision-making, and more efficient workflows. 

Agentic AI Unifies Data and Drives Action

Salesforce’s agentic AI capabilities are designed to simplify complex orchestration across its ecosystem. These intelligent agents help practitioners navigate vast feature sets, automate routine tasks, and unlock insights from unified customer data. 

Perficient’s Salesforce Consulting Managing Director Megan Glasow has seen growing interest in these capabilities, especially as organizations look to consolidate their tech stacks and reduce friction in experience delivery. 

“Salesforce’s consolidation of DXP components paired with tools like Agentforce is helping clients streamline orchestration and unlock hidden data. We’re guiding them through this transformation with a focus on integration and measurable outcomes,” said Glasow.  

Unlocking Business Potential With Perficient and Agentforce. Get the Guide

Using GenAI From Content to Code

Salesforce’s GenAI tools are also enabling marketers to generate personalized content, optimize campaign strategies, and even build applications with minimal coding. These capabilities help teams move faster and deliver more relevant experiences across customer journeys, but speed alone isn’t the goal. As Glasow explains, success with GenAI depends on thoughtful implementation and alignment with business strategy. 

She said, “We’re helping clients explore how GenAI can reduce manual effort and accelerate personalization. But it’s not just about speed. It’s about aligning AI with business goals and ensuring responsible use.” 

Driving Innovation with Responsible AI Adoption

Successful AI adoption in DXPs requires more than just technology. Organizations must invest in strong data foundations, human oversight, and change management to ensure responsible and effective use of AI. These are areas where we continue to guide clients with strategic consulting and hands-on implementation. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Salesforce. Whether it’s integrating predictive analytics, deploying cognitive copilots, or improving data governance, our teams are leading the way in enabling AI-powered transformation. 

If you’re exploring how to bring AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

See How AI Drives Business Outcomes at Dreamforce 2025

At Dreamforce 2025, teams will demonstrate how AI-powered agents and unified data accelerate decision-making, improve adaptability, and deliver measurable results. Attendees can explore how organizations turn strategy into execution through exclusive experiences, including a happy hour, a keynote watch party, a tasting event, and personalized strategy sessions. 

These events highlight how AI enables leaders to streamline operations, reduce inefficiencies, and maximize return on investment. Visit the event landing page for full details and discover how to lead with confidence in an AI-first business environment. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Salesforce expertise here.  

Contact us to learn more. 

As digital experience platforms (DXPs) evolve, Adobe continues to lead the way in embedding artificial intelligence to help organizations deliver more personalized, efficient, and scalable customer experiences. Forrester’s report, The Impact of AI on Digital Experience Platforms, explores how vendors like Adobe are integrating agentic AI and generative AI (GenAI) to streamline experience operations and empower practitioners. 

Adobe is among the leaders in this space, offering tools that help teams simulate ideas, analyze impact, and activate personalized experiences across channels, all within a unified platform. 

Agentic AI Turns Insights Into Action

Adobe’s DXP ecosystem, including Adobe Experience Platform and Adobe Sensei, is increasingly powered by agentic AI — intelligent agents that support marketers and developers in orchestrating and optimizing customer journeys. These agents are designed to reduce manual effort, surface actionable insights, and automate tasks across the experience lifecycle. 

Perficient Adobe Consulting Principal Robert Sumner has seen firsthand how Adobe’s orchestration capabilities can be extended to deliver more seamless digital experiences across platforms. 

“Adobe’s suite enables orchestration to happen naturally across its tools, but we often help clients go further by integrating these capabilities across platforms to create a seamless journey,” said Sumner.  

Creativity Meets Efficiency With GenAI

Adobe is also at the forefront of GenAI innovation. From generating brand-consistent content to enabling marketers to build data-driven briefs and presentations within Microsoft 365 via Adobe’s copilot, GenAI is transforming how teams create and collaborate. 

Sumner mentioned that Adobe’s GenAI tools are already delivering measurable impact for clients. He said, “We’re seeing Adobe’s GenAI tools help clients scale content creation and experimentation. But success depends on aligning these capabilities with business goals and ensuring strong governance.”  

Perficient Named 2025 Gold Globee® Winner for Best Artificial Intelligence Service Provider | Learn More

Responsible AI Adoption

Adobe’s AI capabilities are powerful, but success depends on strong data foundations, human oversight, and change management. That’s why we work closely with clients to ensure these pillars are in place, enabling responsible and effective adoption of AI. 

We’re honored to have contributed to the research in an interview for Forrester’s report , The Impact of AI on Digital Experience Platforms. We believe it reflects our deep expertise in helping enterprise clients implement and optimize DXPs like Adobe. Whether it’s integrating predictive analytics, deploying cognitive copilots, or improving data governance, our teams are leading the way in enabling AI-powered transformation. 

If you’re exploring how to bring AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

Access the report here (available to Forrester subscribers or for purchase).  

Learn more about our Adobe expertise here.  

Contact us to learn more. 

We’re proud to announce that we’ve earned our 8th Adobe specialization in Adobe’s Real-time Customer Data Platform. This milestone reflects our continued commitment to delivering exceptional digital experiences and deepens our already robust Adobe partnership.

View our other specializations in the Adobe partner directory.

What is Adobe’s Real-time CDP?

Real-time Customer Data Platform is a powerful solution that enables organizations to unify customer data from multiple sources in real-time, creating actionable profiles that drive personalized, omnichannel experiences. As customer expectations continue to rise, Real-time CDP empowers brands to activate their data with precision, speed, and relevance.

Why This Specialization Matters

Achieving an Adobe specialization is no small feat. Adobe’s rigorous program evaluates partners on their technical expertise, successful implementations, and proven customer impact. This new Real-time CDP specialization validates Perficient’s ability to architect and deploy scalable data solutions that help clients unlock the full potential of their customer data.

Delivering Real-time Impact Across Industries

Our team has already helped leading brands across industries leverage Adobe’s Real-time CDP to:

• Break down data silos and unify fragmented customer information
• Build real-time, privacy-compliant customer profiles
• Activate audiences across channels for personalized engagement
• Drive measurable business outcomes through data-driven marketing

“This specialization is a testament to our team’s deep expertise in Adobe Experience Cloud and our ability to help clients harness real-time data to deliver meaningful customer experiences,” said Lynn Brading, Global Adobe Alliance Director at Perficient.

How We’re Innovating and Growing With Adobe

As we continue to expand our Adobe capabilities, this specialization reinforces our position as a trusted advisor for enterprise organizations seeking to modernize their digital ecosystems. Whether you’re just beginning your journey with Real-time CDP or looking to optimize an existing implementation, Perficient is ready to help.

Let’s Connect

Explore our Adobe partner page to learn more about our specializations, success stories, and how we can help you turn data into a strategic advantage.

As artificial intelligence continues to reshape the digital landscape, organizations are seeking clarity on how to strategically integrate AI into their digital experience platforms (DXPs). In its latest report, The Impact of AI on Digital Experience Platforms, Forrester explores how DXP vendors are embedding AI agents to streamline experience operations and expand toolsets — from copilots to code generators. Perficient was proud to contribute its DXP and AI expertise to this research, joining the group of vendors and service providers interviewed for the report. 

“Generative AI (GenAI) is reshaping digital experience platforms (DXPs) by automating content and campaign creation, powering intelligent copilots for marketers and developers, and boosting customer engagement through predictive insights and personalization.” —Forrester, The Impact of AI on Digital Experience Platforms

Why AI Belongs in the DXP Conversation

Today’s tech leaders face a growing challenge: delivering consistent, personalized experiences across a fragmented landscape of devices, channels, and customer expectations. DXPs are uniquely positioned to address this complexity. As Forrester notes, DXPs are rich in customer interaction data, support high-value business outcomes, and serve a diverse set of practitioners — all of which make them fertile ground for AI innovation. 

“DXP is a trove of trusted customer interaction data… Unleashing AI on this data enables organizations to understand audience intent and respond to that intent with irresistible offers.” — Forrester, The Impact of AI on Digital Experience Platforms

And Perficient’s experts agree that DXPs are a great place to start when integrating AI into experience delivery. 

“Marketing and IT leaders are under pressure to deliver personalized, omnichannel experiences at scale, and that’s exactly where DXPs shine. By embedding AI into the core of these platforms, clients can unlock the full value of their customer data and streamline operations across content, commerce, and campaigns,” said Mark Polly, Perficient Principal, Customer Experience Platforms.  

Agentic AI Ushers in a New Era of Experience Operations

The report highlights the rise of agentic AI and how these intelligent agents operate within DXPs to automate tasks, answer questions, and optimize workflows. These agents are transforming how marketers, developers, and content creators interact with their platforms, reducing friction and accelerating time to value. 

Perficient’s experience with orchestration tools and AI agents reinforces this trend. While many vendors offer orchestration capabilities, Perficient often helps clients integrate these tools across their broader tech ecosystem. 

” For marketing and IT leaders, true orchestration moves beyond linear workflows; it’s about integrating platforms like AEM and Optimizely to create a dynamic, responsive system. This integration is the key to driving operational efficiency and gaining the unified insights needed for deeper customer engagement. AI agents play a critical role here, transforming those rigid workflows into the real-time orchestration that a modern customer journey demands. Adoption is still in its early stages, which is where we help clients build a strategic advantage,” said Perficient digital strategy principal Grant Davies. 

Emerging GenAI Use Cases in DXPs

From brand-aware content creation to code generation and experimentation, GenAI is also rapidly expanding its footprint in DXP environments. Vendors like Adobe, Sitecore, and Salesforce are launching copilots and agents that empower users to create, test, and optimize experiences with unprecedented speed and precision. 

Perficient is already helping clients explore these capabilities and align them with business goals. 

Polly said, “We’re seeing real momentum around GenAI use cases in DXP from brand-consistent content creation to intelligent experimentation. These capabilities aren’t just flashy features; they’re solving real business problems like reducing time to market and improving conversion rates. The key is aligning AI with measurable outcomes and ensuring strong governance.” 

Perficient Wins 2025 Artificial Intelligence Excellence Award for GenAI Integrity Accelerator   Learn More

Strategic Adoption Requires Strong Foundations 

Successful AI adoption in DXPs requires more than just technology. Organizations must invest in strong data foundations, human oversight, and change management to ensure responsible and effective use of AI. These are areas where Perficient continues to guide clients with strategic consulting and hands-on implementation. 

We believe our inclusion in the research for Forrester’s report, The Impact of AI on Digital Experience Platforms, reflects our deep expertise in helping enterprise clients implement and optimize DXPs. Whether it’s integrating predictive analytics, deploying cognitive copilots, or improving data governance, our teams are leading the way in enabling AI-powered transformation. 

We’re honored to be interviewed for this research and proud to contribute to the evolving conversation around AI in digital experience. If you’re exploring how to bring AI into your DXP strategy, we invite you to connect with us and keep the conversation going. 

Access the report here (available to Forrester subscribers or for purchase).

Contact us  to learn more. 

While working on one of my projects, I needed to implement an autocomplete box using Mapbox Geocoding APIs in a React/Next.js application. The goal was to filter a list of hospitals based on the selected location. The location results from the API include coordinates, which I compared with the coordinates of the hospitals in my list.

The API returns various properties, including coordinates, under the properties section (as shown in the image below). These coordinates (latitude and longitude) can be used to filter the hospital list by matching them with the selected location.

The API requires an access token, which can be obtained by signing up on the Mapbox platform. You can refer to the Geocoding API documentation for more details. The documentation provides a variety of APIs that can be used depending on your specific requirements.

Below are some example APIs taken from the same link.

# A basic forward geocoding request
# Find Los Angeles

curl "https://api.mapbox.com/search/geocode/v6/forward?q=Los%20Angeles&access_token=YOUR_MAPBOX_ACCESS_TOKEN"

# Find a town called 'Chester' in a specific region
# Add the proximity parameter with local coordinates
# This ensures the town of Chester, New Jersey is in the results

curl "https://api.mapbox.com/search/geocode/v6/forward?q=chester&proximity=-74.70850,40.78375&access_token=YOUR_MAPBOX_ACCESS_TOKEN"

# Specify types=country to search only for countries named Georgia
# Results will exclude the American state of Georgia

curl "https://api.mapbox.com/search/geocode/v6/forward?q=georgia&types=country&access_token=YOUR_MAPBOX_ACCESS_TOKEN"

# Limit the results to two results using the limit option
# Even though there are many possible matches
# for "Washington", this query will only return two results.

curl "https://api.mapbox.com/search/geocode/v6/forward?q=Washington&limit=2&access_token=YOUR_MAPBOX_ACCESS_TOKEN"

# Search for the Place feature "Kaaleng" in the Ilemi Triangle. Specifying the cn worldview will return the country value South Sudan. Not including leaving the worldview parameter would default to the us worldview and return the country value Kenya.

curl "https://api.mapbox.com/search/geocode/v6/forward?q=Kaaleng&worldview=cn&access_token=YOUR_MAPBOX_ACCESS_TOKEN"

The implementation leverages React hooks along with state management for handling component behavior and data flow.

How to Create an Autocomplete Component in React

1. Create a React component.
2. Sign up and apply the access token and API URL to the constants.
3. Create a type to bind the structure of the API response results.
4. Use the useEffect hook to invoke the API.
5. Map the fetched results to the defined type.
6. Apply CSS to style the component and make the autocomplete feature visually appealing.

#constants.ts

export const APIConstants = {
  accessToken: 'YOUR_MAPBOX_ACCESS_TOKEN',
  geoCodeSearchForwardApiUrl: 'https://api.mapbox.com/search/geocode/v6/forward',
  searchWordCount: 3,
};

#LocationResultProps.ts

type Suggetions = {
  properties: {
    feature_type: string;
    full_address: string;
    name: string;
    name_preferred: string;
    coordinates: {
      longitude: number;
      latitude: number;
    };
  };
};
export type LocationResults = {
  features: Array<Suggetions>;
};

#Styles.ts

export const autoComplete = {
  container: {
    width: '250px',
    margin: '20px auto',
  },
  input: {
    width: '100%',
    padding: '10px',
    fontSize: '16px',
    border: '1px solid #ccc',
    borderRadius: '4px',
  },
  dropdown: {
    top: '42px',
    left: '0',
    right: '0',
    backgroundColor: '#fff',
    border: '1px solid #ccc',
    borderTop: 'none',
    maxHeight: '150px',
    listStyleType: 'none',
    padding: '0',
    margin: '0',
    zIndex: 1000,
  },
  item: {
    padding: '5px',
    cursor: 'pointer',
    borderBottom: '1px solid #eee',
  },
};

#LocationSearchInput.tsx

import React, { useEffect, useState } from 'react';
import { APIConstants } from 'lib/constants';
import { autoComplete } from '../Styles';
import { LocationResults } from 'lib/LocationResultProps';

export const Default = (): JSX.Element => {
  const apiUrlParam: string[][] = [
    //['country', 'us%2Cpr'],
    ['types', 'region%2Cpostcode%2Clocality%2Cplace%2Cdistrict%2Ccountry'],
    ['language', 'en'],
    //['worldview', 'us'],
  ];

  const [inputValue, setInputValue] = useState<string>('');
  const [results, setresults] = useState<LocationResults>();
  const [submitted, setSubmitted] = useState<boolean>(false);

  // When the input changes, reset the "submitted" flag.
  const handleChange = (value: string) => {
    setSubmitted(false);
    setInputValue(value);
  };
  const handleSubmit = (value: string) => {
    setSubmitted(true);
    setInputValue(value);
  };

  // Fetch results when the input value changes
  useEffect(() => {
    if (inputValue.length < APIConstants?.searchWordCount) {
      setresults(undefined);
      return;
    }
    if (submitted) {
      return;
    }
    const queryInputParam = [
      ['q', inputValue],
      ['access_token', APIConstants?.accessToken ?? ''],
    ];

    const fetchData = async () => {
      const queryString = apiUrlParam
        .concat(queryInputParam)
        .map((inner) => inner.join('='))
        .join('&');
      const url = APIConstants?.geoCodeSearchForwardApiUrl + '?' + queryString;

      try {
        const response: LocationResults = await (await fetch(url)).json();
        setresults(response);
        console.log(response);
      } catch (err: unknown) {
        console.error('Error obtaining location results for autocomplete', err);
      }
    };

    fetchData();
  }, [inputValue]);

  return (
    <div>
      <div style={autoComplete.container}>
        <input
          style={autoComplete.input}
          onChange={(e) => handleChange(e.target?.value)}
          value={inputValue}
          placeholder="Find Location"
        />

        {inputValue &&
          !submitted &&
          results?.features?.map((x) => {
            return (
              <ul style={autoComplete.dropdown}>
                <li style={autoComplete.item}>
                  <span onClick={() => handleSubmit(x?.properties?.full_address)}>
                    {x?.properties?.full_address}
                  </span>
                </li>
              </ul>
            );
          })}
      </div>
    </div>
  );
};

Finally, we can search for a location using a zip code, state, or country.

Additionally, the reverse geocoding API is used similarly, requiring only minor adjustments to the parameters and API URL. The location autocomplete box offers a wide range of use cases. It can be integrated into user forms such as registration or contact forms, where exact location coordinates or a full address need to be captured upon selection. Each location result includes various properties. Based on the user’s input, whether it’s a city, ZIP code, or state, the autocomplete displays matching results.

Whether you’re building embedded software for next-gen diagnostics, modernizing lab systems, or scaling user-facing platforms, the pressure to innovate is universal, and AI is becoming a key differentiator. When embedded into the software development lifecycle (SDLC), AI offers a path to reduce costs, accelerate timelines, and equip the enterprise to scale with confidence. 

But AI doesn’t implement itself. It requires a team that understands the nuance of regulated software, SDLC complexities, and the strategic levers that drive growth. Our experts are helping MedTech leaders move beyond experimentation and into execution, embedding AI into the core of product development, testing, and regulatory readiness. 

“AI is being used to reduce manual effort and improve accuracy in documentation, testing, and validation.” – Reuters MedTech Report, 2025 

Whether it’s generating test cases from requirements, automating hazard analysis, or accelerating documentation, we help clients turn AI into a strategic accelerator. 

AI-Accelerated Regulatory Documentation 

Outcome: Faster time to submission, reduced manual burden, improved compliance confidence 

Regulatory documentation remains one of the most resource-intensive phases of medical device development.  

• Risk classification automation: AI can analyze product attributes and applicable standards to suggest classification and required documentation. 
• Drafting and validation: Generative AI can produce up to 75% of required documentation, which is then refined and validated by human experts. 
• AI-assisted review: Post-editing, AI can re-analyze content to flag gaps or inconsistencies, acting as a second set of eyes before submission. 

AI won’t replace regulatory experts, but it will eliminate the grind. That’s where the value lies. 

For regulatory affairs leaders and product teams, this means faster submissions, reduced rework, and greater confidence in compliance, all while freeing up resources to focus on innovation. 

Agentic AI in the SDLC 

Outcome: Increased development velocity, reduced error rates, scalable automation 

Agentic AI—systems of multiple AI agents working in coordination—is emerging as a force multiplier in software development. 

• Task decomposition: Complex development tasks are broken into smaller units, each handled by specialized agents, reducing hallucinations and improving accuracy. 

• Peer review by AI: One agent can validate the output of another, creating a self-checking system that mirrors human code reviews. 

• Digital workforce augmentation: Repetitive, labor-intensive tasks (e.g., documentation scaffolding, test case generation) are offloaded to AI, freeing teams to focus on innovation. This is especially impactful for engineering and product teams looking to scale development without compromising quality or compliance. 

• Guardrails and oversight mechanisms: Our balanced implementation approach maintains security, compliance, and appropriate human supervision to deliver immediate operational gains and builds a foundation for continuous, iterative improvement. 

Agentic AI can surface vulnerabilities early and propose mitigations faster than traditional methods. This isn’t about replacing engineers. It’s about giving them a smarter co-pilot. 

AI-Enabled Quality Assurance and Testing 

Outcome: Higher product reliability, faster regression cycles, better user experiences 

AI is transforming QA from a bottleneck into a strategic advantage. 

• Smart regression testing: AI frameworks run automated test suites across releases, identifying regressions with minimal human input. 
• Synthetic test data generation: AI creates high-fidelity, privacy-safe test data in minutes—data that once took weeks to prepare. 
• GenAI-powered visual testing: AI evaluates UI consistency and accessibility, flagging issues that traditional automation often misses. 
• Chatbot validation: AI tools now test AI-powered support interfaces, ensuring they provide accurate, compliant responses. 

We’re not just testing functionality—we’re testing intelligence. That requires a new kind of QA.

Organizations managing complex software portfolios can unlock faster, safer releases. 

AI-Enabled, Scalable Talent Solutions 

Outcome: Scalable expertise without long onboarding cycles 

AI tools are only as effective as the teams that deploy them. We provide specialized talent—regulatory technologists, QA engineers, data scientists—that bring both domain knowledge and AI fluency. 

• Accelerate proof-of-concept execution: Our teams integrate quickly into existing workflows, leveraging Agile and SAFe methodologies to deliver iterative value and maintain velocity. 
• Reduce internal training burden: AI-fluent professionals bring immediate impact, minimizing ramp-up time and aligning with sprint-based development cycles. 
• Ensure compliance alignment from day one: Specialists understand regulated environments and embed quality and traceability into every phase of the SDLC, consistent with Agile governance models. 

Whether you’re a CIO scaling digital health initiatives or a VP of Software managing multiple product lines, our AI-fluent teams integrate seamlessly to accelerate delivery and reduce risk. 

Proof of Concept Today, Scalable Solution Tomorrow 

Outcome: Informed investment decisions, future-ready capabilities 

Many of the AI capabilities discussed are already in early deployment or active pilot phases. Others are in proof-of-concept, with clear paths to scale. 

We understand that every organization is on a unique AI journey. Whether you’re starting from scratch, experimenting with pilots, or scaling AI across your enterprise, we meet you where you are. Our structured approach delivers value at every stage, helping you turn AI from an idea into a business advantage. 

As you evaluate your innovation and investment priorities across the SDLC, consider these questions: 

1. Are we spending too much time on manual documentation?
2. Do we have visibility into risk classification and mitigation?
3. Can our QA processes scale with product complexity?
4. How are we building responsible AI governance?
5. Do we have the right partner to operationalize AI?

Final Thought: AI Demands a Partner, Not Just a Platform 

AI isn’t the new compliance partner. It’s the next competitive edge, but only when guided by the right strategy. For MedTech leaders, AI’s real opportunity comes by adopting and scaling it with precision, speed, and confidence. That kind of transformation can be accelerated by a partner who understands the regulatory terrain, the complexity of the SDLC, and the business outcomes that matter most. 

No matter where you sit — on the engineering team, in the lab, in business leadership, or in patient care — AI is reshaping how MedTech companies build, test, and deliver value. 

From insight to impact, our industry, platform, data, and AI expertise help organizations modernize systems, personalize engagement, and scale innovation. We deliver AI-powered transformation that drives engagement, efficiency, and loyalty throughout the lifecycle—from product development to commercial success. 

• Business Transformation: Deepen collaboration, integration, and support throughout the value chain, including channel sales, providers, and patients. 
• Modernization: Streamline legacy systems to drive greater connectivity, reduce duplication, and enhance employee and consumer experiences. 
• Data + Analytics: Harness real-time data to support business success and to impact health outcomes. 
• Consumer Experience: Support patient and consumer decision making, product usage, and outcomes through tailored digital experiences. 

Ready to move from AI potential to performance? Let’s talk about how we can accelerate your roadmap with the right talent, tools, and strategy. Contact us to get started. 

In today’s data-driven world, understanding how users interact with your application is no longer optional , it’s essential. Every scroll, click, and form submission tells a story, a story about what your users care about, what they ignore, and where they might be facing friction.

This is where event tracking and analytics come into play.

Traditionally, developers and product teams rely on third-party tools like Google Analytics, Log rocket, or Hot-jar to collect and analyse user behaviour. These tools are powerful, but they come with trade-offs:

• Privacy concerns : You may not want to share user data with external services.
• Cost : Premium analytics platforms can be expensive.
• Limited customization : You’re often restricted to predefined event types and dashboards.

 What Is Event Tracking?

Event tracking is the process of capturing and analyzing specific user interactions within a website or application. These events help you understand how users engage with your product.

 Common Events to Track:

• Page Views – When a user visits a page
• Button Clicks – Interactions with CTAs or navigation
• Scroll Events – How far users scroll down a page
• Form Submissions – When users submit data
• Text Inputs – Typing in search bars or forms
• Mouse Movements – Hovering or navigating with the cursor

Why Is It Important?

The primary goal of event tracking is to:

• Understand user behaviour
• Identify friction points in the UI/UX
• Make data-informed decisions for product improvements
• Measure feature adoption and conversion rates

Whether you’re a developer, product manager, or designer, having access to this data empowers you to build better, more user-centric applications.

In this blog, I’ll give you a high-level overview of a custom Event Tracker POC built with React.js and Bootstrap—highlighting only the key snippets and how user interactions are tracked.

1. Reusable Event Tracker Utility:

   const eventTracker = (eventName, eventData = {}) => {
     const key = 'eventCounts';
     const existing = JSON.parse(localStorage.getItem(key)) || {};
     existing[eventName] = (existing[eventName] || 0) + 1;
     localStorage.setItem(key, JSON.stringify(existing));
     const event = {
       name: eventName,
       data: eventData,
       timestamp: new Date().toISOString(),
     };
     console.log('Tracked Event:', event);console.log('Event Counts:', existing);};
   

    

2. Wherever event happen add in below format(e.g: form submit)

   eventTracker('Form Submitted', { name, email });

    

3. To view any event tracker count and which event it is, we can do as per below code.

   export const getEventCount = (eventName) => {
     const counts = JSON.parse(localStorage.getItem('eventCounts')) || {};
     return counts[eventName] || 0;
   };
   
   

    

4. Usage in dashboard

   import { getEventCount } from '../utils/eventTracker';
   
   const formSubmitCount = getEventCount('Form Submitted');
   const inputChangeCount = getEventCount('Input Changed');
   const pageViewCount = getEventCount('Page Viewed');
   const scrollEventCount = getEventCount('Scroll Event');
   
   

   This allows you to monitor how many times each event has occurred during the users session  (if local storage is retained).

Advantages of Custom Event Tracker:

1. Full Control – Track only what matters, with custom data structure
2. Data Privacy – No third-party servers, easier GDPR/CCPA compliance
3. Cost Effective – No subscription, suitable for POCs and internal tools
4. Custom UI – Fully customizable dashboard with React and Bootstrap
5. No External Dependencies – Works offline or in secure environments
6. Easy Debugging – Transparent logic and flexible debugging process

Conclusion:

1. If your focus is flexibility, cost-saving, and data ownership, a custom event tracker built in any framework or library (like your POC) is a powerful choice—especially for MVPs, internal dashboards, and privacy-conscious applications.
2. However, for quick setup, advanced analytics, and visual insights, third-party tools are better suited—particularly in production-scale apps where speed and insights for non-developers matter most.

• Use custom tracking when you want control.
• Use third-party tools when you need speed.