Custom AI applications, end to end.
Customer-facing AI products, internal copilots, AI-native SaaS. We design, build, and deploy AI applications that ship — and stay shipped — with the architecture, observability, and ownership you'd expect from software you'd actually rely on.
Five categories of AI applications we build.
Chat & assistants
Conversational interfaces grounded in your data, brand voice, and product context.
Copilots & in-product AI
AI features inside an existing product surface, accelerating the user's primary task.
AI search & discovery
Semantic, citation-grounded search across your content corpus.
Agents & autonomous workflows
Multi-step systems that complete operational work end to end.
Generative tools
Product features that produce content — text, image, code, structured data — on demand.
Embedded AI features
AI capabilities added to your existing product. Lowest scope, often highest impact.
Most AI apps are made of these building blocks.
A typical project picks 2–4 and combines them. We have dedicated pages on each.
Retrieval (RAG)
Grounds answers in your documents, with citations and evals.
Agents
Multi-step systems that use tools to complete work autonomously.
Private LLMs
Self-hosted models for sovereignty, compliance, or cost.
Workflow automation
Operational automations with humans in the loop.
Vector & search
Semantic search, hybrid retrieval, citation grounding.
Document intelligence
Parsing, OCR, extraction from messy real-world documents.
From idea to live AI app in six steps.
Discover
Use case audit, success criteria, model selection, build-vs-buy assessment.
Design
Architecture, data flow, UX, evaluation framework, security posture.
Prototype
Working spike on real data within 2–4 weeks. Validates the hardest unknown first.
Evaluate
Golden dataset, eval harness, A/B testing, human-in-the-loop QA.
Deploy
Production rollout with observability, rollback plan, monitoring dashboards.
Scale
Continuous optimization, fine-tuning, capability expansion, model migrations.
How AI application projects engage with us.
- Use case audit + architecture
- Working prototype on real data
- Cost/timeline model + go/no-go
- Full architecture across all layers
- Eval harness + integrations
- Phased rollout + 30-day support
- Quarterly model migration evals
- Prompt + eval iterations + new capabilities
- On-call + monthly reports
Common questions.
AI app vs. regular app with AI features?
Hosted models or private LLMs?
How long does a build take?
Will I own the code?
How do you handle evals?
What about hallucinations?
Tell us about the AI app you want to build.
A 30-minute call. We'll talk through what you're trying to accomplish, what's been tried, and what the right next step is — Discovery, Prototype, or straight to Production.