AI Digital Transformation

It’s Groundhog Day: Lack of an Integration Strategy Will Inhibit AI, Too


The undisputed hottest topic in technology now and for the near future is LLMs and Generative AI. There’s a lot of talk about how to design prompts and get ChatGPT4 to do cool things for you, but not a lot about how to get value across an entire enterprise. 

That’s what we’ve been up to with our R&D team at Green Irony.

Killer Use Cases Beyond the Imagination

Today’s Generative AI capabilities unlock high-ROI use cases that were unthinkable a year ago. Green Irony’s R&D team has many in the works that we can’t wait to show you. For now, imagine the following scenario in the Travel & Hospitality industry:

A business traveler named Chris is currently in Dallas for some client meetings. It’s summertime and not only is there significant demand for air travel but there is also severe weather including tornadoes, hail, and severe thunderstorms wreaking havoc on the major airline hubs of the midwest. This passenger has a family emergency and needs to get back to Tampa, FL as soon as possible, no matter the cost.

Prior to November 2022’s release of ChatGPT, this would have required a sophisticated travel agent with expert knowledge of flight and rental car booking systems and lots of time with Google Maps and other utilities. Possibly even a spreadsheet, and who wants to use one of those?

What if instead Chris could just say this to an AI service?

“Give me your top 3 options for getting me from my current location to Tampa, FL, by 5 PM tonight. Car travel should be limited to 120 miles or less. Optimize first for arrival time, then for premium seat availability, then for driving distance. Do not risk any connecting flights in the midwest.”

So what’s stopping us from doing this RIGHT now?

Hint: It’s the same thing that always stops us, and MuleSoft Founder Ross Mason was prescient enough to warn us about it for AI in 2018.

Last decade’s disruptor: Mobile and Tablet Devices

2013 saw a huge shift of web traffic from desktop to mobile and this was incredibly impactful to businesses, especially those like retail that rely on web funnel conversion metrics as key business drivers. Mobile was arguably the first major disruptor that truly exposed the perils of siloed enterprise technology systems and lack of a clear, scalable integration strategy. 

I remember seeing it first hand. As my team and I worked with retailer HHGregg to deliver the #1 mobile experience in their space, what do you think our biggest inhibitor was to providing this exceptional customer experience?

If you said “integration”, you’re catching on to the theme of this blog. Attempting to get the right data to drive the right mobile user interactions and respond to these user actions within systems of record was by far our biggest inhibitor. Despite the fact that web browsers and JavaScript frameworks to drive the right mobile behaviors were still considered “cutting-edge” back then (Angular 1.2 was released November 15, 2013!), they were still the easy part. 

Integration was our clear-cut biggest hurdle to creating an award-winning e-commerce mobile experience for our partners at HHGregg.

Today’s Landscape for Scalable Integration

History again repeats itself, but this time with much higher stakes. Insert your preferred doom and gloom messaging about AI and existential risks to the viability of businesses and a high-stakes, zero-sum game arms race here.

The needle simply has not moved fast enough for most organizations over the past decade in terms of scalable integration. Most of them now are stuck with Ross Mason’s “big ball of mud” and every project, big or small, becomes bogged down by this situation. 

Just about every conversation I have with customers about a failed Salesforce implementation comes down to one thing: lack of access to data and business capabilities in other systems. Most of the time, in-house IT teams have built some Frankenstein’s Monster set of data synchronization capabilities that fail to scale with the purchase of new systems and software, evolution of business processes, and marketplace disruptions due to new cutting-edge technologies. In an ironic twist of fate, their Salesforce implementation team tends to spend their time attempting to solve systems integration problems that are not solvable within the Salesforce platform itself.  

These Salesforce implementations are inhibited by the same challenges we saw with mobile e-commerce websites in 2013.

AI will be no different, because today’s LLM’s like OpenAI’s GPT4 heavily reward enterprises with composable integration strategies.

Anybody Heard of This ChatGPT Thing?

Enter the most disruptive technology any of us will ever see in our lifetimes, a technology disruptive enough to disrupt even Google’s core business

Clearly, it’s important for businesses to get this right, and the sooner they get it right, the greater their competitive advantage will be. But without a scalable, composable API strategy that unlocks the capabilities of the business for consumption, broader AI efforts won’t get off the ground. 

In the aforementioned article from Mason, he wrote the following:

“Organizations first need to become more composable, building a connected nervous system called an application network, which enables AI to plug in and out of any data source or capability that can provide or consume the intelligence it creates. The point-to-point integrations of the past won’t be practicable in the AI-world, where things can change in an instant. Instead, organizations need a much more fluid approach that allows them to decouple very complex systems and turn their technology components into flexible pieces.”

Our R&D efforts with OpenAI, which we plan to showcase extensively in the coming weeks, have reinforced Mason’s point of view on this topic. GPT-4, the engine behind ChatGPT, can generate fantastic answers to questions that rely on generally available, non-specialist knowledge. In order to equip it with Enterprise-wide capabilities, we need composable APIs that allow us readily-available access to business capabilities so that GPT can solve real, enterprise-level problems. 

It’s Groundhog Day and we’ve seen this all before. Every innovative breakthrough levies additional burdens on an IT organization’s integration strategy. With the game-changing nature of AI, composable integration is needed now more than ever before.

We’ve Got So Much More to Say On This Topic

We hope you enjoyed the first post in this series. At Green Irony, scalable integration is in our DNA and we are incredibly passionate about this topic and the benefits it provides to our customers. Future posts will cover:

  • A real-life, in-production application that Green Irony has used to exponentially scale its candidate interview process and save hundreds of hours across key members of staff while increasing its applicant quality.
  • A prototype for the Travel & Hospitality industry that unlocks a vastly superior way to purchase products and services in this industry.
  • Several deep dive spotlights into the engineering behind both solutions, showcasing how the Green Irony OpenAI Connector can be used broadly for any OpenAI use case.
  • A comprehensive white paper on why composable integration is an absolute must for companies who are serious about leveraging AI that builds upon the concepts in Ross Mason’s 2018 blog.

Supercharge your AI readiness by combining our MuleSoft OpenAI Connector with an AI-ready integration strategy.

Digital Transformation Platform Migration & Modernization

Slack Is Not a Chat Tool

Slack Is Not a Chat Tool

“But I use it to chat with my entire organization every day!”

You sure do. In fact, if your company uses Slack, you likely use it as a chat tool hundreds or even thousands of times per week. 

You also likely have an iPhone or Android device within two feet of you right now that you use hundreds or even thousands of times per week. How much do these devices have in common with a rotary telephone? 

Breaking Paradigms

One of the iPhone’s core, foundational use cases is basic calling. If the iPhone didn’t do that core use case well, it never would have replaced the Motorola Razr that lived in my pocket in 2009. Its initial value, to me as a consumer, was that not only could it replace my Razr, but it could also replace my iPod and provide a superior SMS experience. 

That was 2012. Do you think my personal paradigm around my iPhone has shifted since then?

Of course it has. Like everyone else, I’ve come to rely on the iPhone to manage my day-to-day life. But what does this have to do with Slack?

One of Slack’s core, foundational use cases is basic chat. If Slack didn’t do that core use case well, it never would have replaced GChat within our organization in 2018. Its initial value, to me as a business owner, was that not only could it replace GChat, it could also replace “internal Green Irony” SMS messaging, add logical channel groupings for focused collaboration, and, of course, add Giphy animated gifs to the mix. Mix in some basic integrations like Google Calendar and it was a no-brainer.

That was 2018. Do you think my personal paradigm around Slack has shifted since then? 

More importantly, do you think Salesforce CEO Marc Benioff shelled out $28 bil for a chat tool with animated gifs? 

The Adoption Problem

Just like starting with calling and text got the iPhone into pockets and at-scale usage to unlock more valuable use cases, Slack started with a chat tool, obtained at-scale usage, and is now at the beginning of the innovation curve where it will unlock much more valuable use cases. Slack will become a staple in putting needle-moving enhancements in the hands of users as quickly as possible to impact key business drivers. It will give users the tools they need to do their jobs much more effectively by providing in-context actions paired with the targeted, rapid collaboration that already takes place within its “chat tool.”

Doesn’t Salesforce already do all this stuff? 

It sure does. In 2017, we wrote that Salesforce is not a CRM. We’ve always seen it as a world-class platform for delivering key business workflows. With five additional years of Salesforce-specific digital transformation experience under our belts since then, what we’ve found is that our biggest challenge in delivering on these promises isn’t the technology platform, it’s adoption. And we’re not alone in this observation.

Within the last month, Gartner has applied a heavy focus on the CRM adoption and data problem with a keynote titled “CROs: It’s Time to Solve the CRM Data Problem.” My key takeaway from this presentation re-enforced what I’ve seen in the field: there’s a “spiral-like” impact between CRM data quality, user experience, and adoption. Poor UX drives low adoption, which drives poor data quality. Poor data quality further magnifies UX challenges, driving even lower adoption. The problem feeds upon itself. And with the CRM more and more connected to the rest of the IT system landscape, the problem is only getting worse. 

The dollars and cents to the business here are immense. This adoption problem exists outside of the CRMs as well, but we’ll narrow the focus to CRMs for this blog. Let’s examine a few examples of the impact of this problem: 

  • Lost rep productivity from sub-optimal tooling and manual workflows, resulting in lower deal size per rep, win rate per rep, and overall revenue per rep. 
  • Poor revenue attainment due to loss of basic or advanced CRM capabilities, depending on severity of issues. 
  • Poor employee experience across key CX-impacting sales and service reps with long-term impact on overall brand equity

No matter the industry, all of these are clearly high-impact areas to a business.  

Salesforce and other CRMs have become more like Systems of Record, catering to “thick work”  like sales forecasting, opportunity management, and complex product support. “Thin work” like collaboration, appointment scheduling, basic task automation, and data entry can pivot to a more natural, in-context usage pattern, solving the adoption issue. 

The Future of Work

We see “thin work” being forced onto users in “thick work” systems is the #1 driver of this adoption issue. We see Slack as THE key technology platform for solving it.

Because its first use case was chat, Slack is already ingrained within users’ day-to-day workflows. It serves as the communication lifeblood of an entire organization. Adoption of productivity-enhancing workflows for users will be a much lesser challenge. These workflows will all produce clean business data, powering more advanced workflows, and, in the future, AI.

Does anyone’s sales organization have a Slack adoption problem? If you’ve heard of one, please reach out and let me know. You’d be the first.

If the key inhibitor to the value proposition of the CRM is adoption, moving pieces of our workflows to a platform with sky-high adoption rates and allowing users to perform actions in-context seems like an area with massive potential. 

A few key questions to ask yourself as a business leader:

  • How could our user productivity and happiness be impacted when we can automate common pain points within our critical revenue-driving and customer-impacting processes? Imagine the at-scale impact of being able to automate the build of a first-call deck so that a rep only has to spend 5 minutes validating and fine-tuning the output.
  • How will our sales KPIs like deal velocity and close rate benefit from our additional rep productivity? Imagine the business impact if reps saved an hour per-day on poor CRM UX and applied that time savings to relationship building, prep, and additional prospecting.
  • How will key EX metrics across reps be impacted by eliminating annoying tooling issues? Everyone’s CRM has a workflow that is hated by every rep because of how much time it wastes. Imagine the morale boost of eliminating it with in-context time-savers in Slack.
  • How will the increased data quality as a result of adoption allow me to better analyze and fine-tune my key business workflows? All of the promises of a fine-tuned CRM that are rarely realized due to adoption and bad data can be realized when these challenges are overcome.

Finally, a question from the blog author: why are very few companies taking advantage of this huge opportunity?

Perhaps we’re just early in the innovation curve and it’s only a matter of time. Or perhaps another reason is a challenge we are all too familiar with: Integration.

Integration Drives Innovation

Through the lens of a CIO charged with innovation, if Slack allows me to design user workflows that impact key business drivers and adoption is no longer a huge challenge, what’s my next challenge?

It has to be integration.

On the technical side, the biggest implication to this type of shift is an even greater strategic need for a scalable integration strategy focused on business agility. We’ll have a need to touch a large number of systems within our technology landscape in order to design the best possible workflows to impact these key business drivers. 

Slack is simply the user control panel, allowing users to perform work in-context more easily. It places an even greater emphasis on what’s happening “behind the scenes” to make the in-context work actionable. We’ll get into the nuts and bolts of what’s required to build custom integrations in Slack in a future blog from Green Irony’s engineering team, but suffice it to say, APIs become much, much more important in this sort of environment. If our goal is to avoid the negative impact of our users wasting time in systems to perform specific in-context actions, we must have a well-designed API network. Without one, the one-off integration requirements levied to the engineering team will kill our delivery timeline and derail our key business priorities. 

This means we need a scalable integration strategy focused on delivering reusable assets that can be used to create a composable business and automating key business processes across the IT landscape. 

Doesn’t this sound like the value prop of something else you’ve seen Marc Benioff acquire in the past five years? 

Betterer Together

We’ve seen the “Better Together” MuleSoft and Salesforce campaign for a few years now. We fully believe in it ourselves, having created a fictional story to highlight the concept at a high-level technically

It’s our view that Slack and MuleSoft are even “Better Together” than the previous pairing. The reason for this is because Slack’s #1 use case in every organization is always going to be chat. But that doesn’t mean it’s a chat tool. It means that savvy organizations with control over their API strategy can leverage this “chat tool” to ensure they conquer the adoption problem that impacts all businesses. Conquering this problem is going to be a bigger and bigger competitive advantage in today’s digital world.  

We’ve written ad nauseum about MuleSoft’s ability to shine in key areas and won’t repeat them here. Some reading for interested parties can be found below:

In a nutshell, MuleSoft allows technology departments to create reusable API assets that model the company’s core business. These assets can be composed into critical business processes and orchestrations of the behind-the-scenes technology interactions required by these processes, dubbed an “Application Network.” These processes can then be surfaced in the exact way necessary for a consumer to interact with them.

This is exactly what’s needed technologically to capitalize on the immense business value unlocked by the Slack platform. This pairing was meant to be.

Are You Prepared for the Future of Work?

All visionary executives must ask themselves one critical question: am I prepared for what’s to come with the future of work? 

If the answer is no, you are essentially relying on your competition to be equally unprepared. Because if they are, you’re toast, aren’t you? Your competition will be ahead of you in several key areas:

  • They will have the business agility to competitively differentiate themselves rapidly under new market conditions such as pandemics, geopolitical situations, or inflationary impacts.
  • They will have a superior set of data upon which to make actionable business decisions and drive future AI scenarios.
  • Their workforce will be much more productive than yours, dollar for dollar.
  • They will be able to continually improve high-impact metrics like revenue, CX, EX, and cost of sale by making the employee workflows and communications that drive these metrics more effective. 
  • They will be able to quickly open new revenue channels and attack new business models without the friction of user adoption.
  • They will see the business results that get organizations to buy into these types of technology platforms and 8-figure “digital transformation” or “modernization” initiatives.

Does this sound like a competitor you want to deal with from your current position, or do you want to win by planning, executing, and evolving?  Talk to us today about gaining your competitive edge through a scalable integration strategy tied to your business outcomes.

Green Irony News

Green Irony’s Commercial Revamp

A Common Sense Approach to Digital Transformation Backed by a 60-year-old Framework

Green Irony has always aligned our organization’s success to our customers. I started the company with a bet that Salesforce provided a superior technology platform that would allow our highly-skilled engineering teams to attack digital transformation initiatives more quickly and effectively. Having to deal with fewer “moving parts” with technology would enable our teams to focus more on other critical factors for delivering successful digital transformation outcomes.

Five years later, I can say that Salesforce’s platforms have not disappointed. Marc Benioff continues to evolve his technology vision and software offerings on the fly, giving organizations better tools than they have EVER had at their disposal for accomplishing their business objectives. Our team at Green Irony, effectively trained on these platforms, is capable of delivering scalable business value FAR faster and with fewer problems than we were without these platforms at our disposal.

There’s a but.

But, we’ve found that it isn’t enough to just be the best at delivering business outcomes using Salesforce and MuleSoft. There was another key set of variables limiting our success, and Green Irony needed a set of well-defined offerings to better address these inhibitors to successful outcomes. 

Digital Transformation Isn’t Just Technology

At its core, digital transformation is about transforming a “normal” corporate entity to operate more like a tech company. Ideally, this transformation merges the advantages of the existing corporate brand with the scale advantage of tech “disruptors.” A well-executed transformation results in the business having fine-grained control over processes that drive critical business metrics impacting revenue and profitability. These goals involve more than merely bringing in software platforms. Does creating a world-class mobile app alone make you Uber? And why do 70% of digital transformations fail?

The answers to these questions lie within the common sense of a 60-year-old framework.

The PPT Framework that was created in the 1960s says, to paraphrase: People, Process, and Technology must live in harmony for an organization to operate at a high level. People do the work and processes govern how they do it. If technology “levels up” significantly through “Tech Modernization,” it stands to reason that the other two elements of the PPT framework would need to support this change.  

Too many enterprises embarking on Digital Transformation ignore this common-sense wisdom.

Customers bring in modern technologies like Salesforce and MuleSoft and expect to wave Marc Benioff’s magic wand over their existing technology landscapes, perform anIT project, and deliver a business outcome fit for Marc’s next Dreamforce keynote. They parachute these shiny new platforms into their existing IT operating environments, say phrases like, “let’s do a base implementation,” and tell their teams to go. Chaos erupts. 

This approach is counterproductive to the organization’s goals.

Under this “strategy,” implementations are executed by People trained to enhance and support the existing legacy Technology. These People, with minimal training, set out to deliver capabilities on new Technology platforms using IT Processes that were defined for the older Technologies. These legacy Processes were also designed with different goals in mind than what’s necessary to succeed at digital transformation. 

People and Process misalignment in digital transformation have caused me to personally witness the following Corporate IT Horror Stories:

  • Customer buys MuleSoft for agility; Enterprise Architecture carves up processes for taking the “Donkey Work” in-house, increasing cost and eliminating MuleSoft’s agility
  • Customer purchases MuleSoft to accelerate development; IT does not train staff on MuleSoft and continues to unknowingly build its own in-house MuleSoft “competitor” on AWS
  • Customer acquires Salesforce to move fast; PMO leverages legacy KTLO processes that stifle innovation and grind the Software Supply Chain to a halt.
  • Customer hires high-end, dedicated platform consulting experts; point-and-click Salesforce administrators call the shots on architectural strategy

These stories will be explored in more detail at a later date, but they all have one thing in common: they have nothing to do with technology. They arise because the Technology leg of the three-legged PPT stool has significantly “outgrown” the other two legs when Salesforce and MuleSoft enter the equation in a technology modernization effort.

So no, we can’t be Uber just by virtue of having a compelling mobile application. Uber has evolved its People, Processes, and Technology in TANDEM to BECOME Uber and OPERATE like Uber. And transformations, even with a great technology platform strategy, fail without the appropriate People and Process to bring that Technology platform strategy into motion the RIGHT way. 

A Modern IT Operating Model

Building world-class People & Process capabilities to match the Technology capabilities of Salesforce and MuleSoft does not happen overnight. At Green Irony, our objective is to help our customers maneuver around this constraint, accelerate their Digital Transformation goals, and EVOLVE these other two legs of the stool as we move through the roadmap.

A well-run digital transformation engagement focuses on getting new business value in the hands of customers as quickly as possible, analyzing data, and rapidly evolving the technology based on the analysis. A successful process for delivering on these goals needs to be agile and it needs to be capable of getting right-sized capabilities to the market quickly. We need fast Software Supply Chain cycle times, continuous feedback on metrics that matter, and continuous evolution of the technology product with capabilities delivered to the end customer regularly.

This type of model is much more Silicon Valley than it is Corporate IT.

Existing Corporate IT operating models are geared toward keeping core day-to-day operations running smoothly and minimizing risk from even small changes. Resources are deployed on siloed projects with rigid schedules and limited visibility into upstream or downstream implications in the software supply chain. There is very little in common between the objectives or operating models used here and those that are used in well-run digital transformation engagement. 

The core operation must keep running smoothly as digital transformation capabilities are released quickly. Therefore, both portfolios of processes are required, each with specific purposes for the organization. 

Green Irony’s Market Response

Green Irony is already delivering exponential value using MuleSoft Anypoint Platform and Salesforce. We’re evolving our offerings and our messaging to fully embrace what we’ve always been: a bridge between your existing IT operation and the business. We operate like Silicon Valley because it’s in our DNA to do so. We provide the People and Processes required to fuel your digital transformation goals while you mature your own internal operating models to match the needs of technology product development. This evolution doesn’t happen overnight, and our offering strategy is focused on ensuring it happens in a way that fuels technology innovation, protects the in-flight technology investment, and sets our customers up for ongoing success.

Our refined commercial offerings and messaging will focus on several key areas:

  • Creating a repeatable Software Supply Chain that rapidly delivers business value to our customers’ customers
  • Measuring, analyzing, and shortening the cycle time of this supply chain, fueling rapid delivery of on-demand capabilities to customers
  • Leveraging technology platforms and tooling that enable the rapid rollout of high-impact business use cases at scale
  • Optimizing future data access using MuleSoft, increasing the “clock speed” of the business by reducing the critical path of the Software Supply Chain

Our mission at Green Irony is to change the way that our customers think of delivering technology and to level up their organization’s ability to accomplish the main goal of digital transformation: Operate like a tech company and combine the advantages of that operating model with their own. These offerings will help our customers do just that.

Platform Migration & Modernization

The Modern Solution to P&C Third Party Data Provider Integration

The Importance of Data To P&C Insurance Carriers

To evaluate the risk of writing a new policy on a property, insurers rely on a vast array of third-party data providers that supply information on important factors like flood risk, replacement cost estimation, potential liabilities like swimming pools, policyholder creditworthiness, and the likelihood of catastrophic events like hurricanes. With a rapidly growing pool of new data providers, the number of data points that can be mixed and matched to increase a carrier’s ability to accurately assess policy risk is growing by the day. 

Proper estimation of risk is a make-or-break proposition for an insurance carrier since it directly impacts the carrier rating, overall profitability, and long-term financial stability. Carriers who underwrite policies with poor risk-to-premium ratios don’t stay in business for long; on the other hand, carriers who invest in a data strategy that allows them to be nimble and leverage risk data to its fullest advantage have a clear leg up on their competition. The evolving availability of data provides a tremendous opportunity for carriers to not only upgrade their ability to estimate risk but also to harness data to detect fraudulent claims, identify risk of policyholder attrition before it happens, surface customer insights, and handle nearly limitless other scenarios.

The ability to properly leverage this data is of the utmost importance to carriers. Unfortunately, carriers are held back by legacy integration approaches that prevent them from maximizing the impact of this data on their bottom lines.

The Traditional Integration Approach

Carriers have been using third-party data to automate portions of the underwriting and risk assessment process for over a decade by wiring services like Melissa Data, Core Logic, and LexisNexis directly into their policy management systems (PMS). The PMS is a monolithic center of the universe in this approach, handling connectivity to the third party providers, aggregating data, applying business logic, and remediating any errors that occur within the transaction before ultimately leveraging the data for its purpose.

In the example below, the Duck Creek PMS consumes data from five different third-party providers and uses custom-developed code to implement the necessary logic within the PMS:

Traditional Integration Approach for Policy Systems

Please note that Duck Creek was chosen for this example and this problem exists for all other policy management systems such as Guidewire. 

This approach silos application and business logic within customizations that live on the Duck Creek PMS. It has several pitfalls from a technology perspective that hamstring business initiatives to more effectively use this data:

    • Critical business logic is siloed and not reusable to other consumers like additional policy management systems, customer-facing portals, or third-party comparative raters, meaning this logic would need to be written, maintained, and governed for each of these additional consumers.
    • Replacing or augmenting a problematic provider results in an IT project that is developer-intensive, slow to market, and costly with an outage risk to the mission-critical PMS.
    • Monitoring and problem determination are challenging, error-prone, and time-consuming since they involve custom code that lives on the policy management system.
    • Legacy third-party data providers have cumbersome interfaces that are difficult to integrate with and troubleshoot, resulting in one-off spaghetti code. 
    • No ability to scale services independently based on throughput needs since they live within a monolithic policy administration system. 
    • Much greater barrier to entry to adding new best-of-breed 3rd party data providers.
    • Decreased ability to intelligently cache and meter pay-per-use 3rd party APIs, resulting in increased spending with these vendors.

These pitfalls result in a severe challenge for carriers looking to leverage available data for making the best business decisions. Because this approach is how things have always been done at most carriers, their mindsets have been molded to believe that this is simply the way things are and that they must live with it. But there is a better way to handle managing these integrations that allow carriers maximum agility, reuse, and speed to market while also mitigating outage risk to the PMS.

The Modern Approach: API-led Integration

The API-led approach to integration is just what the doctor ordered for solving this technology challenge and fueling the next level of intelligent data usage at carriers. API-led Connectivity decouples integration logic from the policy management system, alleviating the challenges with the legacy approach.

Insurance Three-Tiered Architecture

The result is a solution that allows carriers to move much more quickly in replacing or adding new data providers without outage risk, simplifying a very complex and costly scenario:

    • Changing or adding additional 3rd party data providers becomes much less costly and faster without the outage risk to the PMS of the legacy integration approach.
    • Business and application logic becomes reusable to other consumers like additional policy management systems, external comparative raters, and policyholder portals.
    • Robust data monitoring and problem determination capabilities allow IT to rapidly identify and remediate production issues.
    • Each service can be independently scaled to handle its own unique needs.
    • New best-of-breed providers can be added and incorporated into the architecture quickly.
    • Increased governance and metering of pay-per-use data providers.
    • Full ownership and control of data
    • Increased ability to rapidly scale new product lines and regions


As technology continues to evolve with new InsureTechs emerging daily, the need for insurance IT organizations to be nimble and give themselves the ability to leverage best-of-breed data will continue to become more critical to remain competitive. Legacy approaches to integration of these data providers have saddled carriers with IT infrastructure that is slow to adapt, costly, rigid, and poses needless outage risk to mission-critical, revenue-driving policy management systems. API-led connectivity solves the problems posed by this legacy architecture in an elegant way, giving carriers the tools they need to succeed in today’s data-driven landscape.

Need help modernizing your integration strategy? Want to learn more about how API-lead connectivity helps your business? Contact us to start the conversation.