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Lemraj

AI-enabled solutions

Lemraj engages on a small number of AI-enabled solution engagements a year, where production-grade LLM or retrieval systems must operate inside an existing enterprise estate, with the security, evaluation, and human oversight that regulated and audit-bound buyers require.

Who it's for

This service is built for organisations that meet all three of the following:

  • Already operating at scale. A live business operation in insurance, financial services, the public sector, or a comparable enterprise context. AI is being added to a system that already exists, not built as the first line of code.
  • Carrying a real production target. A specific business workflow, regulatory or operational pain point, or internal-knowledge problem where AI is a candidate solution — not a strategic exploration of what AI might one day do.
  • Capable of operating the result. An in-house engineering or platform team that can take ownership of the system Lemraj delivers, with the security, observability, and review processes appropriate to its risk class.

These three conditions describe where Lemraj's AI service tends to be the right fit. If your situation is different, the discovery conversation is the easiest way to find out together.

Where we focus

We focus on organisations that:

  • Need production-grade LLM or RAG systems integrated into an existing enterprise system, with defined security, evaluation, and audit boundaries.
  • Are building internal-knowledge retrieval systems where access control, data lineage, and content governance are first-class concerns.
  • Are integrating AI components inside a larger modernization or integration programme.
  • Want an independent, production-oriented review of an in-flight AI initiative.

Where we are not the right fit

This service is selective by design. We are typically not the right fit for organisations that:

  • Are exploring AI through prototypes or proofs-of-concept without a defined production target.
  • Need a generic chatbot or website-companion build without enterprise integration or governance requirements.
  • Are looking for AI strategy decks, roadmaps, or literacy programmes disconnected from a specific production deliverable.
  • Are at an early stage and have not yet reached the scale where Lemraj's engagement model is justified.
  • See evaluation, audit, and human review as overhead rather than part of the system.

If your AI work sits outside what we focus on, we are happy to recommend other firms that do that kind of work well.

What's included

A typical AI engagement at Lemraj includes some combination of:

  • Production target definition. A written statement of the business workflow the system is intended to support, the failure modes the business cares about, and the success criteria.
  • Architecture and risk design. Model selection, retrieval design, integration boundaries, security model, audit surface, human-review pathways.
  • Implementation. Building the system in collaboration with the in-house engineering team, with infrastructure, observability, and deployment designed to be operated by the client.
  • Evaluation framework. Metrics, datasets, and review processes designed to measure the system against the business target — not against generic AI benchmarks.
  • Operational handover. Runbooks, evaluation dashboards, model-update processes, and the conditions under which the system should be paused, retrained, or retired.

We do not deploy AI systems we cannot evaluate. We do not deploy AI systems with no human in the loop where the failure mode warrants one.

How we engage

  • Typical timing: 2–4 week paid discovery, then 3–6 months for a defined first production deployment.
  • Team shape: Lead architect plus a senior practitioner with AI and evaluation experience for delivery phases. Lemraj does not deploy AI systems that no Lemraj practitioner can evaluate directly.
  • Contracting: Time and materials with defined scope and milestones. Fixed-fee discovery for the entry-point engagement.
  • Engagement size: From €25,000.

Outcomes

A typical AI engagement produces:

  • A first production AI system deployed inside an existing enterprise environment, with defined security, evaluation, and human-review surfaces.
  • An evaluation framework the in-house team can run independently — including the model-update and model-replacement processes.
  • An honest read on where AI helps in the wider system landscape, and where it does not.

We treat AI deployments as production systems, not experiments. The deliverable is something the client's operations team can run.

Where this fits

AI engagements at Lemraj usually run alongside or directly into:

Considering AI inside an existing enterprise system?

A discovery conversation is the easiest way to find out whether the work is a fit — sometimes the honest answer is that AI is not the right intervention for the problem you actually have.

Start a discovery conversation →