LyraGen
AI build studio

Agentic AI for high-trust operations.

We ship production agentic systems for organisations where compliance and auditability matter. Running in your business in weeks.

Start a conversationSee the work
Time-and-materials billingScope estimated up frontStop when the work is complete
Time to production
-
weeks

with LyraGen

vs 6-12 months from scratch

What that includes

Auth, audit, memory, safety middleware, and observability. All in one engagement.

The problem

Off-the-shelf AI breaks down in real operations.

There are four structural gaps between what an operation needs and what off-the-shelf AI delivers.

No specialist routing

When one model handles intake, review, and escalation, context gets lost and the output stays shallow.

No document handling

Real work runs on forms, contracts, and reports. Generic tools cannot handle them at scale.

No persistent memory

Every session starts from scratch. Case history and open threads vanish when the chat closes.

No audit trail

Compliance reviews need permanent records of every decision. Most AI products do not keep them.

The gap we close

A POC is easy. Production is the hard part.

Prototyping is democratised. Claude Code, Cursor, v0. Production isn't. The gap between a working laptop demo and a system running in your business is where most AI projects die.

POC

Happy path demo

2-5 days with Claude Code

Happy path demo
2-5 days with Claude Code
Authentication and user-scoped data
Immutable audit and compliance
Cross-session memory and state
Safety guardrails and escalation paths
Cost controls and rate limiting
Observability and monitoring
Deployment and rollback paths
Scale and reliability
Production · with LyraGen

Production

3-7 weeks with LyraGen

  • Happy path demo (the POC you already have)
  • Authentication and user-scoped data
  • Immutable audit and compliance
  • Cross-session memory and state
  • Safety guardrails and escalation paths
  • Cost controls and rate limiting
  • Observability and monitoring
  • Deployment and rollback paths
  • Scale and reliability
Our approach

Strategy and implementation in one team.

We work like a consultancy on the thinking and like a build team on the shipping. The same people shape the problem and ship the production system.

From scope to production

We own the work from problem definition through to running it in production. Same team throughout.

Start without a spec

You do not need a finished spec to start. We work it through with you and build from there.

Working slice in three weeks

Most of the production stack already exists: orchestration, auth, audit, memory, safety. Configuring it for your domain is the bulk of the work.

What We Build

Four shapes of agentic work.

These are the patterns we see most. Most engagements fit one. For anything else we adapt the shape to the problem.

Interactive intakequalify · askREQUESTSHANDOFF

Interactive intake

Conversational assistants that qualify, triage, and route. Collect what is needed, ask useful follow-ups, escalate to a human when the judgement call belongs to one.

Examples

Clinical triage · legal intake · insurance FNOL

Autonomous research pipelineA1A2A3A4SCHEDULEDPUBLISHED

Autonomous research pipelines

Scheduled ingestion from configured sources. Multi-agent synthesis with human approval gates. Structured publishing on a fixed cadence.

Examples

Newsletters · regulatory digests · competitive intel · market briefings

Document intelligenceextractPARTYVALUERISK FLAGGEDUNSTRUCTUREDSTRUCTURED

Document intelligence

Upload documents. Extract the key facts, summarise, flag issues, prepare the next action. Turns stacks of input into structured decisions.

Examples

Claims review · contract analysis · compliance mapping

Workflow orchestrationspecialistspecialistspecialisthubONE ENTRYCALLS & RETURNS

Workflow orchestration

One conversational entry point. Routes work across departments, remembers context, executes the next action.

Examples

IT service desks · internal ops · multi-department support

Case Studies

What we've shipped.

Two production systems. One in healthcare, one in research. Same building blocks, different domains.

Case Study · Healthcare

Multi-agent care navigation.

From first symptom to booked appointment, in one conversation, grounded in NHS source material.

Triages patients, interprets medical records and imaging, and books them into care. Specialist agents handle each step inline. No portal hopping, no forms.

9-agent swarm3-layer safety middlewareNHS-grounded RAGAgent ProtocolJWT authImmutable audit

Specialist agents

Safety layers / response

%

Actions audited

Context lost / session

Case Study · Research

Automated biotech newsletter.

Replaced a manual single-channel workflow with a multi-agent pipeline. Three source channels, five specialist agents, cross-provider fact-checking.

Cost reduction
%

Run cost dropped from around £200/month to £15-£35/month. Fact-checking became more rigorous in the process.

LangGraphBERTopicPrefectPostgreSQL + pgvectorRedis · MinIOFastAPI + HTMXTelegram bot
MetricBeforeAfter
Monthly costaround £200£15-£35
SourcesManual searchRSS + Tavily + Gmail
Story memoryNone, repeatsANN deduplication
Fact-checkingSelf-checkCross-provider, source-verified
ResearchSequentialParallel per-story
SchedulingManual triggersFully automated with approval gate
Talk to us about your problem
How it works

Six building blocks, configured per engagement.

Every deployment starts from the same six building blocks. We configure them around your domain.

Specialist routing

Intent-aware handoff between domain sub-agents. One front door, many specialists behind it.

Persistent memory

Context that survives across sessions. Users do not repeat themselves. Memory controls for transparency and UK GDPR compliance.

Immutable audit

Database-level triggers prevent modification or deletion. Every tool call and decision is logged permanently. Defensible under regulator review.

Safety middleware

Layered guardrails: content filtering, output validation, escalation rules. Fail-closed on sensitive operations.

Document intelligence

Upload. Extract, summarise, flag issues. RAG retrieval from your knowledge base.

Action execution

Books, schedules, escalates, notifies. The system completes the task and writes the result to audit.

What you get

Faster delivery, lower run cost, audit-ready, no lock-in.

What an engagement delivers, in business terms.

To production

3-7 weeks

Working software in your team's hands. The production stack already exists, so we configure rather than rebuild.

Predictable economics

Lower run cost

Cost controls and rate limiting from day one. Real workloads, real budgets. LyraNews dropped from around £200/month to £15-£35/month.

Audit-ready by default

Compliance built in

Immutable logs, fail-closed safety, DSAR-ready data controls. Built with NHS clinical safety standards in mind.

No lock-in

Model-agnostic

Built on open-source orchestration with model-provider flexibility. Switch providers as pricing and capability change.

How We Engage

How we engage.

Every engagement is different. The way of working stays consistent. You see progress early. You stay in control of what happens next.

01

Understand the problem

We start by building a shared picture of the problem. Scoping and prototyping happen in the same conversation, because the infrastructure already exists and we can explore while we define. Output is a working direction you would actually approve.

02

Ship incrementally

You see something real within two to three weeks. A working slice, a data pipeline running against your sources, a first interface. We extend it week by week. Simple engagements ship in weeks. Complex ones run a few months.

03

Stop when the work is done

The engagement ends when the work is done. Pause and evaluate, wrap, or extend. No phases padded to use up budget. Ongoing support is available if you want it.

Scope estimated up front · Time-and-materials billing · Additional scope priced transparently

Team

An experienced team. You work with us directly.

No account managers, no sales layer. The people who scope the work are the people who build and ship it.

Gleb, Delivery Lead at LyraGen
Your point of contact

Gleb

Delivery Lead

Owns the engagement end to end and leads delivery across scope, timelines, and client communication. Makes sure discovery turns into a pilot, and the pilot has a clear path to production. Keeps projects focused on what was promised at the start.

Talk to me about scope and delivery.

Danil, AI Engineer at LyraGen

Danil

AI Engineer

Designs the multi-agent architecture behind LyraGen engagements: specialist routing, memory, safety, and retrieval. MSc in Data Science. AI delivery experience from Accenture across financial services, public sector, and NGOs.

Talk to me about agent architecture.

Ilia, Full-Stack Engineer at LyraGen

Ilia

Full-Stack Engineer

Builds and runs the systems behind LyraGen engagements: frontend, services, and infrastructure. Computer Science MSc. Production experience in deployment, monitoring, and scheduling that keeps systems running after launch.

Talk to me about shipping and infrastructure.

FAQ

Common questions.

If yours is not here, send it over. We read everything.

Contact

Tell us what you're trying to ship.

We reply within two working days, and tell you whether your problem is one we can help with.

01

Reply within 2 working days.

From whoever can give you the most useful answer.

02

30-minute scoping call.

Thirty minutes to work through the problem. We push back if the ask is not quite right.

03

Scope and estimate within a week.

Within a week, you have an estimate and a clear yes or no.

Or write to hello@lyragen.co.uk directly.

We do not share your details. We reply within two working days.