Solutions

Four ways we apply the research.

Applied AI work on a problem that does not yet have a product attached to it. Every one of these is anchored to research we own and a platform already running in production: so you are not paying us to form an opinion from scratch, or to rebuild retrieval and evaluation for the fourth time. They stack in the order below, and most programmes use two of them.

SOL 01

DeepTech

The four engagements

What each one is for, and what you get back

SOL 01

DeepTech

DTRIHub. DeepTech Research & Intelligence Hub

For problems where the method does not exist yet. We take your question into the research track with university research groups and PhD advisors, prove or disprove the approach against a stated baseline, and tell you which it was, including when the answer is that you should not build it.

Method designBaselinesPrototypes Claim areasJoint programmes

Inside DTRIHub → Request an advisory call →

Start here ifYou have tried the obvious approaches and they do not hold up on your data.

We deliverA written research question, a reviewed method, a prototype measured against a baseline, and a decision on whether to file.

Who joinsPhD advisors on method, domain advisors on the problem, our engineers on the build.

IPBackground and foreground IP separated in writing before work starts.

ShapeA programme with review gates. A prototype that misses its baseline is written up and stopped. A normal outcome, not a failure.

Leads toA method that ships into lalla.ai, or a clear reason not to continue.

SOL 02

Data Spine

Data strategy, and your domain modelled as a graph

A spine is what everything else hangs off. Most data strategy work ends with a platform diagram and a governance deck; ours ends with your domain modelled as a typed graph, because that is what lets a model reason over how things connect rather than over rows — and it is the asset every later AI project reuses instead of rebuilding.

Domain graphData contractsLineage QualityLakehouseMaster data

Request an advisory call → How graphs are used →

Start here ifData sits across many systems and there is no single trustworthy view of the thing you actually operate.

We deliverA typed domain graph, contracts between producers and consumers, quality and lineage, and an honest list of what you still cannot answer.

Different becauseThe spine is designed to carry AI workloads later, not only dashboards now. It is the same modelling approach EUNIQ and TopSyllabus run on.

Also coversPipelines, lakehouse design, master data and the reporting layer.

ShapeAssessment, then a build phase your team can take over.

Leads toAI Engine, with the hard part already done.

SOL 03

AI Engine

AI engineering, built on lalla.ai

Finding the use cases worth doing, then building them so they survive a security review and an operations handover. We start from a platform already in production behind two products, so the first months go into your domain instead of into rebuilding retrieval, evaluation and guardrails for the fourth time.

AgentsCopilotsRetrieval EvaluationGuardrailsMLOps

Request an advisory call → Inside lalla.ai →

Start here ifYou have pilots that impressed everyone and changed nothing.

We deliverA scored use-case roadmap, working software against real data, an evaluation harness, and an operations handover with runbooks.

Different becauseEvidence, guardrails and evaluation come from the platform on day one rather than being retrofitted when security asks.

Also coversModel selection, applied AI engineering, MLOps, and change management for the teams who will use it.

ShapeStaged, with a named output and a stop-or-continue decision at each gate. Nothing runs open-ended.

Leads toA system your operations team owns, not a pilot we keep alive for you.

SOL 04

Cloud Mesh

Cloud strategy: designed around where data may live

Cloud decisions are now AI decisions. Residency, sovereignty and cost per token decide what you are able to build at all. Most enterprises are not on one cloud either, they are on several, plus on-premise, plus something a regulator will not let move. We design for that mesh rather than pretending it away.

Landing zonesKubernetesSovereign On-premiseZero trustFinOps

Request an advisory call → See what we deploy →

Start here ifA regulator, a ministry or a board has told you where your data may and may not go.

We deliverLanding zones, an AI-ready reference architecture, security architecture and identity, and a cost model that survives scale.

Different becauseWe run our own products in sovereign, on-premise and air-gapped environments, so this is not theoretical for us.

Also coversSecure SDLC, audit evidence, migration and platform engineering.

ShapeAssessment and target architecture, then delivery with your team alongside.

Leads toAn environment where the AI work is allowed to run in production.

Looking for something you can license?

Products are listed separately

EUNIQ, TopSyllabus and the lalla.ai platform are finished things with a price attached. Cybersecurity and supply chain sit under Partner Platforms.

Products → Partner platforms →

Start here

Bring one problem. We will tell you if it is worth building.

Thirty minutes with the engineers who would do the work. No deck, no discovery invoice, a straight read on feasibility, sequence and what a first build would take, including when the answer is that you should not build it.

Request an advisory call → Solutions → Products →

30 min · video call Who joins · engineering, not sales Cost · none