Platform & Cloud

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Our approach

With little formal documentation to lean on, Coherent’s team relied on frequent, direct conversations with the client’s technical staff to confirm new features as they completed each step of the project:

• Codebase archaeology and consolidation: engineers worked through the four mismatched mobile repositories, cross-referenced them against the live app store build, and reconstructed the most current working codebase before making any changes.
• Environment separation: introduced dedicated development, QA, and production environments in place of the single, undifferentiated setup the client had been running.
• Cloud infrastructure cleanup: rebuilt cloud build pipelines and restructured infrastructure, improving reliability, while bringing monthly cloud costs down from roughly $8,000 to about $1,500, an 81% reduction.
• New device API: built a new backend API, on a Grails and Java/Spring stack, that takes raw measurements from the client's new refraction-testing hardware, applies the client's formula, and returns validated results ready for review by a licensed doctor.

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The solution

Today, the platform supports a complete at-home vision-testing workflow. Users complete a guided assessment with the client's hardware, results are processed through Coherent-built backend logic, and outcomes are routed to a licensed eye care professional for a prescription. The underlying infrastructure now runs across separate dev, QA, and production environments at a fraction of its previous cloud cost, giving the client a stable foundation to build on as it brings new devices to market.

 

The impact

• 81% reduction in monthly cloud costs, from about $8,000 to about $1,500
• New device API delivered in about 9 months, supporting the client's newest hardware line
• New development, QA, and production environments to replace the client’s single setup, consolidating four mismatched mobile repositories into one working codebase

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The challenge

An undocumented, fragmented codebase

Before building the API or writing new code, Coherent needed to identify the code currently driving the client’s companion app. With no product requirements documentation and four mismatched repositories to sort through, they had to cross-reference what was on old developer laptops against the live versions in the app stores.

No environment separation and rising cloud costs

The client’s systems and software were running in a single environment — without a clear separation between development, QA, and production — which increased the likelihood of issues like cascading errors. Additionally, cloud infrastructure spend was disproportionate to the size of the product, running close to $8,000 per month.

New hardware, new math

The client was bringing a new device to market that paired with the user’s smartphone and measured refractive error using patented optical technology. Coherent needed to build the backend logic that would take the client's proprietary formula, apply it to raw device measurements, and return an accurate, prescription-ready result.

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What's next

Through AKTIV, Coherent’s dedicated fitness and wellness practice, the company will continue to support the client’s ongoing platform enhancements across mobile, backend, DevOps, QA, and project management. Using the same consumer healthtech context that shaped the client’s rebuild, AKTIV's engineers will also ensure the client’s hardware, app, and backend continue to evolve together as the device line matures.

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Our approach

As the client's partner, Coherent Solutions engineered an NLP solution that analyzes online product reviews. Aspect-based sentiment analysis makes it possible to see which product characteristics customers react to, and how, across a large set of reviews.

Cloud engineering and scalable data processing allowed the solution to handle the large volume.

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The solution

Coherent Solutions contributed:

• AI and machine learning engineering for a natural language processing solution built on aspect-based sentiment analysis
• Data processing designed for large volumes of customer feedback
• Cloud engineering supporting scalable data processing
  
  
  

The impact

The engagement produced the following results:

• Sentiment identified for specific product characteristics
• Product strengths and weaknesses identified from customer feedback
• Customer feedback processed at scale

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The challenge

Reviews often mention several characteristics of a product in the same text, each with its own opinion. An overall review score or sentiment label cannot capture that, and the client needed to know what customers thought about individual characteristics of each product.

The work covered hundreds of thousands of online product reviews, so the solution had to process customer feedback at scale.

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What's next

How we worked here is how we work on every engagement. Whatever form your data takes, we start with the questions you need answered, select the right approach, and engineer the data processing and cloud deployment so the answers are ready to be used.

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Our approach

Coherent started inside the lender's existing teams and moved into ownership as the engagement proved out. The lender's engineering managers ran delivery at the outset and brought Coherent in for capacity. That changed, stream by stream, into accountability for outcomes.

Taking loan origination out of the vendor's hands

The vendor that built the loan origination platform had customized it for the lender and continued to develop and support it. The lender asked Coherent to move that development onto our team.

The vendor had no reason to move quickly. Its own processes governed how requirements were confirmed and how work shipped, and its contract paid it for the work being transferred away. For close to a year the two teams ran in parallel, at first on the same stories, with scope released to Coherent's side only as far as the vendor's position allowed. Our delivery lead worked inside that arrangement, learning how the implementation had been built and why, while the team put its engineers through the certifications the platform requires. When the vendor's contract ended, the whole of it sat with Coherent.

We own development and releasing today, with three developers and a QA engineer on the stream. DevOps sits on the lender's side with a Coherent engineer inside that team, and the lender keeps approval rights over what ships. The lender has been rebuilding how it plans and releases, so the team now works to a different process than the one the vendor ran.

Scoping a checkout the lender would own

The lender is now scoping a checkout process of its own, to replace the part of the vendor platform it actually uses. The monthly licensing and hosting bill covers the whole product, not the portion the business runs on.

The lender has started making this concrete. It brought in a product owner dedicated to the rebuild, and it is planning to grow the team so one group supports the existing process while another builds the new checkout.

Consolidating on Salesforce while keeping legacy supportable

Salesforce is the lender's strategic system of record, and five teams work on it. The newest product was built Salesforce-only from the start, which set the direction for what follows. A new partner portal, close to release, connects directly to Salesforce and bypasses the older partner API.

The legacy PHP systems still carry core processes, so the work there is about keeping them safe to run. Coherent upgraded the partner API to a supported PHP version, and the older platform continues to serve the products that depend on it while the lender decides how to retire it.

Simplifying integration and data

Coherent's integration work reduced the number of connections the lender has to own.

• An event bus carries traffic between internal systems and out to third parties on a publish and subscribe standard. A payment event reaches every subscribed system without bespoke wiring.
• Credit, identity, document intelligence and background data now arrive through a single gateway rather than a direct integration per provider, from sources including Experian, Plaid, Ocrolus and LexisNexis.
• Mambu orchestrates accounts and payments between Salesforce and the payment systems, including bank responses.
• Snowflake consolidates the databases behind every system, and a dedicated team builds curated views. A team needing data from several sources reads one view instead of many databases.
  
  

Establishing QA and release standards

Coherent's QA lead owned quality across the lender's entire delivery organization, internal and external teams alike, for roughly 18 months, until the lender hired a permanent QA director. The work concentrated on the rollback problem, covering how releases are tested, what has to be true before one ships, and which standards apply to every team rather than to one. Scrum practice was strengthened alongside it.

Putting AI into the delivery workflow

Developers work in Cursor, and QA adopted it for test case authoring. The lender approved the tooling and provided the licenses, which matters for a lender with compliance exposure on how code and test artifacts are produced.

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The solution

The lender now has a delivery organization with standards and one strategic direction for its platform. The application path runs end to end. An application arrives from direct sales or a partner, data on the business and its owner returns through the single gateway, the backend calculates a risk score, and a go or no-go decision follows. Approved merchants receive offers, negotiate terms and sign contracts, funding runs through the lender's bank agreements, and collections tracks payments against schedule.

Three surfaces sit around that path.

• A merchant portal where borrowers see account history and payments, request a promise to pay, and generate their own monthly statements.
• A new partner portal wired directly to Salesforce, replacing an older portal and the API hop behind it.
• A case manager application that receives merchant-run checkout submissions and approves or declines them.
  
  

The organization around the software changed as much as the software did. QA and release standards are documented and shared, and loan origination has an accountable delivery owner inside Coherent rather than at a vendor.

 

The impact

This work left the lender with capabilities it did not have before, and a transaction that depended on them.

• Business readiness. The lender's technology leadership spent this period preparing the company for a transaction with a private-equity buyer. That transaction completed, and Coherent's engineering and process work supported the readiness behind it.
• Delivery no longer runs on a vendor's timetable. Loan origination changes ship on the lender's schedule, released by a certified team accountable for the outcome rather than for a support contract.
• Releases stopped being a risk event. Rollback-free releases are the explicit target across every delivery team, measured against one documented standard where there previously was none.
• Adding a data provider is a one-place change. A new credit, identity or document source no longer means another point-to-point integration to own and maintain.
• Answering a data question no longer requires knowing the estate. Curated views replaced the need to track which of many systems held which field.

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The challenge

The lender had outgrown the way it built software. Growth had added systems, teams and integrations faster than it added the documentation and standards to coordinate them, and leadership recognized the company could no longer run the way it had at a quarter of the size.

Five problems shaped the engineering agenda.

• Two CRMs, one business. A Salesforce implementation and a PHP platform built more than a decade earlier both ran in production. For older products, sales sat in Salesforce while underwriting, collections and payments stayed in the legacy platform.

• Manual underwriting and slow decisioning. Prequalification and approval depended on manual steps and on data pulled individually from each credit, identity and document provider.

• Releases that rolled back. Testing happened in UAT, defects surfaced in production, and rollbacks followed. On live funding and payment flows, each one carried operational cost.

• No shared record of how anything worked. Onboarding, handover and incident response all depended on the people who happened to remember.

• A bought platform that did not fit. Loan origination ran on an off-the-shelf digital lending product, customized for the lender by the vendor that built it. The architecture did not match how the lender works, the application carried a large set of features the business never used, and support and hosting fees continued regardles

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What's next

The checkout rebuild is the next substantial piece of work, and it is not ready to start. The lender wants development underway early next year, which means requirements and a first set of stories have to exist before this year ends. The team has seen a two-page outline so far, which means the schedule depends on analysis that has barely started.

The migration off the legacy platform is planned rather than underway. The lender is weighing the cost of moving the remaining products into Salesforce against the cost of upgrading the legacy platform's PHP version, and core processes still depend on the old platform. Meanwhile the new partner portal is close to release and AI-assisted delivery is expanding from development into QA.

This engagement shows where modernization tends to lead at a company that grew faster than its documentation. Two years in, the question in front of the business is no longer how to modernize a platform it bought. It is which parts of that platform it should own outright.

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