Generative and agentic AI, industrial automation, MLOps and LLMOps, and the full-stack engineering underneath all of it. Commissioned as one build, or one service at a time.
Three of these five layers have no model in them. We build those too.
In brief
Custom AI & Digital Build is the engineering practice at EigenSpark. We build AI systems to a company’s own requirement, and we build the digital and technology platforms underneath them, including the ones with no AI in them at all. The work covers generative and agentic systems, industrial AI, model operations, application development, integration, data platforms and modernisation. It is delivered against your systems, in your environment, and it is finished when it is carrying real traffic.
What we build
Models, agents, the infrastructure they need, and the operations that keep them honest once they are live.
The second track is technology and digital engineering, and it is sold on its own. Application development, integration, data platforms, cloud engineering, design, modernisation, testing and ongoing operation. Companies commission that work with no AI attached, and it is roughly half of what we ship.
The tracks meet more often than they separate. An assistant is only as good as the integration feeding it, and a model that cannot reach your data is a demonstration. One team builds both sides, so there is no seam to hand across.
The services
Grouped by track. Nothing in the second group depends on anything in the first.
Models, agents, the infrastructure they run on, and the operations that keep them accurate.
Assistants, drafting, summarisation and retrieval over your own documents, with the source cited.
→Systems that take an action, with a human approval step where it matters.
→Vision, sensor and process models that run on the plant floor.
→The compute, networking and environments a model needs before it can serve traffic.
→Training, deployment, monitoring and retraining, so a model does not quietly decay in place.
→Prompt versioning, evaluation, cost control and guardrails for anything built on language models.
→The platform work, delivered standalone. Commissioned with or without any AI alongside it.
Web and mobile applications built to carry real load from the first day.
→Connecting the ERP, the core platform, and the ten systems nobody ever documented.
→Pipelines, warehouses and lineage, so the same number means the same thing in two departments.
→Environments, pipelines and releases that go out on a Tuesday without a war room.
→Interfaces designed around what the operator actually does, then tested with the people who do it.
→Moving a platform that still runs the business, without stopping the business.
→Automated coverage that catches the regression before your customer reports it.
→Running what is live: monitoring, fixes, upgrades, and a named person on call.
→Our AI & Digital Products Suite
Eight products, each one started as a custom build. Where one covers your case, we will say so.
Analyses every sales conversation, updates the deal strategy, and coaches reps until they improve.
→Our LMS and course creation tool, built on the material you already have.
→Reads PDFs, scans and forms in whatever format they arrive in, extracts the fields that matter, and sends each one into the right workflow.
→Reads a contract, finds the clauses that carry risk, and compares them against your standard.
→Takes a name and a city, researches the buyer, and returns a profile with the lead scored and tiered.
→Forecasts demand and flags the shipment about to run late, with the reason attached.
→Reads sensor data and calls the failure before the line stops.
→Checks records against the rule set as they arrive, and keeps the evidence trail behind it.
→How it runs
What the system must do, what it connects to, and what will count as working. Written down and agreed before anyone opens an editor.
Working software in front of you at short intervals. You review the running thing, never a picture of it.
Into your systems, your identity provider, your network rules. This is the stage most pilots never reach.
Monitoring, retraining, and the changes the business asks for once real people are using it.
Related
A full-stack platform and an integration layer, delivered as an engineering project.
→ PillarThe engagement that decides which of these is worth commissioning.
→ PillarGetting your own engineers fluent in what has been built.
→ IndustryWhere the largest share of this build work happens.
→ How we workHow an engagement runs from the first call to production.
→ ProductsEverything already built, with what each one does.
→FAQs
Yes. Each one is scoped and priced independently. A data platform, an integration layer or a test automation suite is a complete engagement on its own terms. None of them requires the AI work beside it.
Regularly. A good share of what we ship is application development, integration and platform work with no model anywhere in it. We do not add AI to a project so that it fits our positioning better.
You do. Source, infrastructure definitions, documentation, and model weights where the model is ours to hand over. Where a third-party model sits inside the system, you hold that contract with the provider directly.
Yours, in nearly every case. We work inside your accounts, your identity provider and your network rules. Where a regulator requires the data to stay on hardware you control, the system is designed for that from the first day.
Fixed scope where the requirement is genuinely clear, and a rate-based engagement where it is not. We say which one applies before you commit. We do not quote a fixed price against a scope we already expect to move.
Send us the requirement, however rough. You will get a scope, a shape, and an honest read on the hard part. We reply within 48 hours.
Talk to us