Design it. Prove it. Ship it.

Model Fine-Tuning & Customization

Frontier parity on your domain, on weights you own.

Off-the-shelf models are generalists. We take open weights and specialize them — distillation plus LoRA/QLoRA — until they match the frontier on the exact workflows your business runs on, with none of the per-token bill. Proof: a local OLMo-3.1-32B with LoRA reached parity with Claude Opus 4.8 on the hardest in-domain workflows, trained on 312 validator-clean examples curated by best-of-N distillation.

Capabilities

Evaluation & Observability

Trust nothing unmeasured.

Vibes are not a metric and self-grading is not a test. We stand up independent judge panels, model scorecards, and hallucination detection so every claim about quality is checked by something other than the team that shipped it. Proof: we cut a frontier model’s cost ~52% and latency ~74% while maintaining quality — gated by a separate judge model, not by opinion.

Capabilities

AI Safety & Alignment

Never validate a delusion.

Money-on-the-line and human-on-the-line systems need adversarial testing before they meet a user, not after. We build safety harnesses, crisis-routing logic, and red-team suites that judge the agent on its verbatim words. Proof: a voice-safety harness routed 4 of 4 crisis categories to a human, scored against exactly what the agent said, not what we hoped it meant.

Capabilities

Sovereign / Private AI

The full agent loop on a box you control.

Reasoning, tool-calling over MCP, memory, RAG, even voice — the entire loop running on open models on hardware the customer owns. No data egress, no per-token meter, a cost you can predict. Proof: a self-hosted ~32B model at frontier level, parked for about $16/month, with zero data leaving the box.

Capabilities

AI Governance & Compliance

Auditability the regulator will accept.

In regulated domains the output has to be traceable, scoped, and defensible — not just plausible. We build citation traceability, document mapping, deterministic validators, and human-in-the-loop where the regulator requires it. Proof: biologics CMC proposal authoring across CTD Module 3, with deterministic validators as a hard quality gate on every claim.

Capabilities

Conversational & Voice AI

Real conversations that move real money.

Voice agents that authenticate a caller, take a card payment, work a fraud case, and switch languages mid-call without dropping context. Proof: Aura/Auralis handles live payment calls end to end, built on Pipecat, LiveKit, Deepgram, and ElevenLabs, with self-hosted XTTS v2 when the voice has to stay on-prem.

Capabilities

RAG & Document Intelligence

Retrieval that reads the page, not just the text.

Documents are layout, tables, and stamps — not a flat wall of text. We build late-interaction visual retrieval that understands the page as it looks, plus structured extraction that turns messy files into clean data. Proof: Harvestor does visual retrieval over layout, tables, and stamps with ColQwen2.5 and LanceDB, and extracts structure from resumes and invoices.

Capabilities

Agentic / Multi-Agent Systems

Plan, act, remember, hand off.

Agents that decompose a goal, call the right tools, keep memory across steps, and hand off cleanly between specialists. Proof: Nexus and an on-chain A2A marketplace coordinate multi-agent plan / tool-call / memory / handoff flows, built on PydanticAI, LangGraph, Google ADK, and MCP.

Capabilities

Generative Media

Renders that match a real SKU.

Generative imagery is easy to make and hard to make accurate. We build media pipelines that stay faithful to a real product, not a hallucinated one. Proof: Agam produces catalogue-accurate renders that match an actual SKU, built on gpt-image-2 and FLUX.

Capabilities