Generative AI applications
Product features powered by models: drafting, summarizing, classifying, extracting: inside the workflow, not beside it.
AI engineering
AI development services that reach production
Most AI projects stop at the demo. Ours are built to be operated: grounded in your own data, measured against real cases before launch, with a cost ceiling and a human approval step wherever the risk sits. You get a feature your business can rely on, not a pilot that impresses once.
Overview
We build AI features on top of your own data, with evaluation and guardrails from day one: assistants, document and knowledge systems, AI agents that complete multi-step work, and multi-agent systems where one agent is not enough, with human review where the risk sits. Answers you can trace, cost you can forecast, behavior you can change.
- Generative AI applications
- AI agents & multi-agent systems
- Evaluation & guardrails
- AI adoption strategy
Problems we solve
- Knowledge is trapped in documents
- Teams re-answer the same questions because the answer lives in a PDF, a ticket or someone's head.
- Pilots never reach production
- A demo that works on ten examples has no evaluation, no cost ceiling and no owner. It stops at the pilot.
- Nobody can explain the output
- Without retrieval and tracing, an answer cannot be checked, so the business cannot rely on it.
What we build
AI assistants
Grounded question answering over your documents and systems, with citations back to the source.
AI agents & multi-agent systems
Multi-step work with tool and API calls, one agent or several coordinating, run under explicit limits and human approval where the risk sits.
Evaluation & guardrails
Test sets, regression runs, cost ceilings and monitoring, so behavior changes only when you decide it should.
Typical use cases
- Internal knowledge assistant over policies and documentation
- Document intelligence: extraction, classification and review queues
- Support triage and drafted replies with human sign-off
- Intelligent search across product, CRM and content systems
How we deliver
- 01
Discovery
A scoped session to agree the problem, the constraints and the metric that will move.
- 02
Design & architecture
The smallest structure that solves it, written down before anyone writes code.
- 03
Build
Two-week increments with something reviewable at the end of each one.
- 04
Run & improve
Monitoring, iteration and a handover your own engineers can carry.
Technology we use
- OpenAI API
- Anthropic API
- Retrieval (RAG)
- Evaluation sets
- Agents with human review
- pgvector
Proof from the portfolio
Three products where a language model does real work inside the product (preparing content, structuring knowledge, planning) with the guardrails that keep a person in charge of what it claims.
AI marketing workspace
Merlin Studio
An AI marketing workspace where strategy, brand knowledge and content live in one place, and a person approves the final version.
See the projectAI matching platform
Work Transcendence
A knowledge graph of what a person knows, where every claim keeps the sentence that proves it, matched to real work requirement by requirement.
See the projectAI product
LifeCopilot
A project execution system that turns a brief into sized tasks and tells you whether the deadline is real.
See the projectFrequently asked questions
- Do we need our own model?
- Almost never. Most value comes from retrieval, tooling and evaluation around a hosted model. We recommend training only when a measurable gap justifies it.
- How do you control cost?
- We instrument token and call cost per feature from the first week and set ceilings, so spend is a forecast rather than a surprise.
- What about accuracy?
- We build an evaluation set from your real cases before launch and run it on every change, so quality is measured rather than assumed.
How to buy this
AI work is sold as a scoped project or inside a monthly arrangement.
Related capabilities
Started with Lovable, Bolt, v0 or Cursor?
Run the free production-readiness audit first
If your app was generated by an AI builder, the first question is not which service you need. It is what the codebase is hiding. Paste the URL, get the report in a minute. If one thing is broken, we fix that single problem rather than selling you a project.
From the products we build
Free tools and guides from software we built and run ourselves.
- worktranscendence.comThe EU AI Act and hiringWhy recruitment AI is treated as high-risk from August 2026, and five questions to ask any vendor.Read it
- worktranscendence.comFour ways an AI screener misleads youAnd the one question that catches all of them, as a checklist you can use on any scoring tool.Read it
- pigeonatlas.comEmail for agents: send only to people who askedWhat has to be true before an AI agent is allowed to send email from your domain.Read it
Keep going
Where to go next
- Read the case studiesChallenge, solution and measured outcome from delivered engagements.Continue
- Calculate project costA guided technical discovery that returns a budget range, timeline and team shape.Continue
- Book a strategy callForty-five minutes with the engineers who would actually build it.Continue
AI engineering
Talk to us about AI engineering & strategy
Tell us the problem and the deadline. You will speak to an engineer, not a sales team. We typically reply within 48 hours.
