Practical AI that earns its keep.
RAG copilots, document intelligence, automation agents and custom LLM workflows — grounded in your data, evaluated on real tasks.
Everything you'd expect — and the bits most agencies skip.
- RAG Knowledge Assistants
Internal copilots that answer from your docs, tickets, wiki and Slack — with citations.
- Document Intelligence
Extract structure from invoices, contracts, forms and emails. JSON in, decisions out.
- Automation Agents
Multi-step agents that draft, route, summarise and act inside your existing tools.
- Custom LLM Workflows
Prompt orchestration, evaluation harnesses, guardrails, tool-use, function calling.
- Voice & Speech
Whisper-powered transcription, voice notes, real-time translation, call summarisation.
- Evaluation & Safety
Test sets, regression tracking, PII handling, prompt injection defences.
A predictable four-stage process.
Use-case scoping
Identify the highest-value tasks and define what 'good enough' looks like.
Data & eval set
Index your data; build an evaluation set so improvements are measurable.
Build & iterate
Ship a working v1 in weeks, not quarters. Iterate against the eval set.
Operate
Logging, observability, cost controls, prompt-versioning, ongoing tuning.
Tooling, not religion.
We pick the right tool for the job. Here's what we reach for most often.
Common questions about generative ai solutions.
Will my data be used to train models?
No. We default to providers and configurations where customer data is not used for training, and self-host models when policy requires it.
How do you avoid hallucinations?
Retrieval grounding, function-calling, structured outputs, confidence thresholds and human-in-the-loop on high-stakes actions.
Can you self-host?
Yes — we deploy open models (Llama, Mistral) on AWS, Azure or your own VPC when data residency demands it.