Book a 30-minute discovery call. We'll map the workflow, data, product idea, or operational bottleneck — then define the AI application, agent, automation, or private system worth building first.
Book an AI discovery call ↗A 30-minute working session for teams that need an AI application, agent, automation, internal tool, or private model. We map the workflow, find where AI pays for itself, and shape the first system worth building — before production spend begins.
AI readiness audits and a clear, prioritized roadmap of where AI actually pays off.
Open models — Llama, Mistral, Qwen, Gemma — deployed on your own infrastructure.
High-performing agents for support, research, document Q&A and multi-step workflows.
Complete AI-powered web and mobile products, from first prototype to production.
Ingestion, embeddings, retrieval and the plumbing that makes AI reliable.
Wiring AI into the tools you already use, with ongoing monitoring and improvement.
Private document Q&A, drafting, research and client knowledge workflows.
Risk workflows, support triage and sensitive customer data automation.
Patient/admin workflows, appointments and private knowledge assistants.
Lecture processing, student support, research tools and admin automation.
Email, support, reporting and internal workflow automation.
Compliant, sovereign AI for sensitive public-service operations.
AI that pays for itself.
Most AI projects die as demos — impressive in a pitch, invisible on the P&L. We start from the other end:the workflow, the hours, the cost.
We identify where AI actually pays off in your business, then build the system — application, agent, automation, or private model — and ship it into your real operations. When your data or compliance demands it, we run everything on your own infrastructure. The measure of success is simple: hours saved, cost cut, revenue unlocked.
JTI built us an AI system that runs entirely on our own servers. Data stays here, costs are predictable, and it actually works.
— Dominic Damoah, Founder & CEO · 300ML
intelliQ needed the complete AI engine behind a voice-first study platform — GPU-accelerated transcription, LLM-powered note generation, a grounded AI tutor, and a six-queue job system. We built every piece: private Parakeet ASR on EC2, Claude structuring pipeline, vector-grounded tutor, Go image search service, and five product surfaces students use every day.
Read case study →hitl.sh is building the infrastructure that keeps humans in control of AI — a platform where developers pause agent decisions and route them to human reviewers. We built their complete internal admin surface: real-time request monitoring, user and loop management, API key provisioning, Stripe billing, audit logging, and an email campaign system — all in one control plane. Recognised with a 2025 Webby Award for Best Responsible AI.
Read case study →By the end, you'll know what AI system is worth building, what the first useful prototype should be, and what it would cost.