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Production AI that delivers ROI, not demos.
A prompt in a playground is not a product. Real users ask questions your test set never covered, hallucinations become support tickets, token costs scale faster than revenue, and nobody can prove the thing is actually accurate. Shipping AI is an engineering discipline — retrieval quality, evaluation suites, guardrails, and cost control — not a prompt-writing exercise.
We build AI features that survive contact with real users: retrieval-augmented assistants, document intelligence, and custom agent workflows. Grounded in your data, evaluated rigorously, and deployed with guardrails — then integrated into the software your team already uses.
See the full technology stack we work with.
If one of these sounds like your situation, we've likely solved a close version of it before.
Staff ask questions in plain language and get sourced answers from your policies, contracts, and documentation instead of searching folders.
Extract structured fields from invoices, applications, and reports at volume, with confidence scores and human review for edge cases.
Support and sales assistants grounded strictly in approved content, with escalation paths and answer logging.
Summarisation, drafting, classification, and semantic search added to software you already run in production.
Automating document-heavy and support workflows routinely saves teams 20+ hours per week.
Customers and staff get instant, sourced answers instead of digging through docs.
AI built on your proprietary data is an asset competitors can't copy.
Identify where AI delivers measurable ROI in your workflows.
A working proof-of-concept on your real data within weeks.
Accuracy benchmarks, guardrails, and red-teaming.
Production rollout with usage and quality dashboards.
The questions we get asked before every engagement — including the pricing ones.
AI work is quoted in two stages, because nobody can responsibly price a production system before seeing your data. A scoped proof-of-concept on your real data typically starts around $2,000–$5,000 and takes a few weeks — it establishes what accuracy is actually achievable and what the production build requires. Production systems with evaluation suites, guardrails, and integration into your existing software usually run $8,000–$20,000 depending on data complexity and any compliance requirements. Both stages are quoted fixed-scope and shaped to your project.
Something not covered here? Ask us directly — you'll get an engineer, not a sales rep.
Book a free scoping call. We'll map your workflows against what AI can reliably do today, and tell you honestly which ideas aren't worth building yet.
Average response time: under 4 business hours