We build and scale SaaS products, recommendation and analytics platforms, and internal tooling for insurance and software firms across the UK and worldwide.
Insurance and SaaS businesses run on software that has to keep working as they grow. More users, more touchpoints, more integrations, and a growing pile of internal tooling that has to keep pace. We build and scale the products and platforms behind that growth, from customer-facing apps to the recommendation engines, analytics layers and operational tooling that sit underneath them.
Stratatech is an independent digital product consultancy based in London, working with clients across the UK and worldwide. We bring a single cross-functional squad of product, design and engineering people to each engagement, so the team that scopes the work is the team that ships it. You see something real early and the feedback loop stays tight, which matters when you are launching a new product or untangling a system that has grown faster than its architecture.
Most SaaS work splits into two layers. There are the digital products people interact with, the apps and portals where they do the thing your software is for, and there are the digital platforms underneath that let you add features and serve new use cases without rebuilding from scratch each time. We work across both. Some clients come to us with a Figma file and a deadline, others with a working product that needs to scale or a backlog that has outgrown the original design.
For Leesman Index we turned Figma designs into a production-ready hybrid working insights platform and launched it to over 10,000 survey participants. The detail is in the Leesman Index case study. Taking a design to a live product at that scale is its own discipline: the interface has to hold up, but so do the data model, the survey pipeline and the reporting underneath it.
Personalisation is one of the clearest ways a SaaS product earns its keep, but it works best as a shared service rather than logic copied into every app. For AllBright Collective, a global women's network, we built a graph-powered recommendation API that serves multiple apps and touchpoints from one place. The same engine personalises content, events and connections wherever members are, so the experience stays consistent and the recommendation logic lives in one well-tested service. You can read more in the AllBright Collective case study. We design recommendation and data APIs the same way for other clients: a clear contract, a sensible data model, and room to evolve the ranking without breaking the apps that depend on it.
A lot of SaaS value is locked up in data, and getting it out in a usable form is harder than it looks. An analytics or insights platform has to ingest data reliably, model it in a way that answers real questions, and present it so people trust what they see. The Leesman work is one example, where the product exists to turn survey responses into workplace insights at scale. We build the pipeline, the storage and the reporting layer together, so the numbers people act on are the numbers the system actually holds.
Operations work tends to start as manual tickets and stay that way long after it should. For Convex Insurance we built a serverless admin platform that automates Slack channel provisioning and governance for global teams, replacing a queue of manual admin requests with a reliable, auditable workflow. The Convex Insurance case study covers how it works. Serverless suits this kind of problem well: the workload is spiky, the logic is event-driven, and there is no reason to run servers waiting for the next request. We use the same approach for other operational automation where a team is spending time on work a system should be doing.
Internal systems age quietly. A CRM or analytics dashboard that was fine three years ago becomes slow, brittle and risky to change, and the team works around it instead of with it. For Darktrace we modernised an internal CRM and the analytics dashboards alongside it, improving performance, security and maintainability while integrating external services and adding automated background jobs. The Darktrace case study has the specifics. Darktrace is a cyber-security AI company and our work was on their internal tooling, not their security products. We take the same approach to other internal systems: make them fast and safe to change, wire in the integrations the business actually needs, and move the manual steps into automated jobs.
Scaling a SaaS product is rarely about raw traffic alone. It is about adding clients, features and integrations without the system becoming fragile, and about a team that can keep shipping safely as the product grows. We invest in the things that make that possible: observability so you can see what the system is doing, audit trails so you can answer who did what, and a developer experience that makes changes safe to make and easy to ship.
We weigh these trade-offs deliberately rather than reaching for the fashionable answer. Our platform engineering guide sets out how we think about it, and the same judgement shapes the digital platforms we build for clients.
What we do and what we don't
We are a software and platform consultancy. We build and modernise products, platforms and internal tooling for insurance and SaaS businesses. We are not an insurer and we do not provide regulated insurance or financial services. Where we have worked with a cyber-security client, that work was on their internal tooling, not on security testing or security products. We are clear about that line from day one so there are no surprises later.
We built a serverless admin platform that automates Slack channel provisioning and governance for global teams, replacing manual admin tickets with a reliable, auditable workflow.
We built a graph-powered recommendation API that serves multiple apps and touchpoints, enabling AllBright to personalise content, events and connections for its members.
We turned Figma designs into a production-ready hybrid working insights platform, launched to over 10,000 survey participants.
We improved performance, security and maintainability of Darktrace's internal CRM and analytics dashboards, while integrating external services and automated jobs.
We build and scale software-as-a-service products and the platforms underneath them: customer-facing apps and portals, the data and API layers that power them, and the internal tooling that keeps a business running. Recent work includes a graph-powered recommendation API for AllBright Collective and a hybrid working insights platform for Leesman Index, launched to over 10,000 participants.
Yes. For AllBright Collective we built a graph-powered recommendation API that serves multiple apps and touchpoints, so the same engine personalises content, events and connections wherever members are. We design recommendation and personalisation as a reusable service rather than logic buried inside one app, which keeps it consistent across your product surfaces.
Yes. For Darktrace we modernised an internal CRM and analytics dashboards, improving performance, security and maintainability while integrating external services and adding automated background jobs. We do similar work where teams are slowed down by ageing admin systems, replacing manual processes with reliable, auditable workflows.
We design for the kind of scale your product actually faces: more users, more touchpoints and more integrations, without the system becoming fragile. We use serverless and event-driven patterns where they fit, build in observability and audit trails, and invest in developer experience so the team can ship changes safely. Our platform engineering guide goes into the trade-offs we weigh.