LLMs wired into
systems that already run
We integrate language models where they remove real work: retrieval over your own documents, automation of queues a person currently clears by hand, and inference you can host yourself when the data cannot leave your perimeter.
AI engineering capabilities
Model choice is the smallest decision on the list. The work is in retrieval quality, output validation and what happens when a call fails.
LLM integration into existing systems
Model calls wired into the software you already run — CRM, ERP, ticketing, internal portals — behind a service boundary, with retries, cost accounting and a fallback path when the provider degrades.
RAG pipelines over your own data
Ingestion, chunking, embedding and retrieval tuned to your document structure. Answers cite their source, and the index is rebuildable from the original files at any time.
Document and text automation
Classification, extraction, summarisation and normalisation of documents that currently move through a human queue. Structured output validated against a schema before it reaches your database.
Workflow automation
Multi-step processes where a model handles the judgement and deterministic code handles everything else. Each step is observable, replayable and reversible.
Prompt engineering and fine-tuning
Prompt versioning, evaluation sets and regression checks before a change ships. Fine-tuning only where prompting and retrieval genuinely run out of headroom.
Self-hosted inference
Open-weight models such as Llama and Mistral served on your own hardware or private cluster, for workloads where data cannot leave the perimeter.
Models, retrieval & serving
Providers are interchangeable by design — the integration layer is ours, so a model swap is a configuration change rather than a rebuild.
What runs under the hood
- Node.js
- TypeScript
- React 19
- REST / streaming APIs
- PostgreSQL
- Vector indexes
- ClickHouse
- Object storage
- Docker
- Kubernetes
- Worker pools
- RabbitMQ / Kafka
- OpenTelemetry
- Sentry
- Structured logging
- Cost dashboards
Connected expertise
Have a process that should not need a human queue?
Describe the workflow, the data it touches and where it currently stalls. We will come back with a scoped integration plan and an honest view of what a model can and cannot take over.