DIGITAL KITCHEN
CUSTOM AI DEVELOPMENT

Custom AI Development. When Off-the-Shelf Won't Work.

Bespoke AI builds for businesses with specific data, specific workflows, or specific compliance needs that ChatGPT-as-a-product cannot meet.

Custom AI development means building software that wraps an LLM around your specific data, workflows, or compliance needs, instead of buying a generic SaaS that nearly fits. We build custom RAG systems, multi-agent platforms, AI-powered SaaS features, and internal AI tools. Most projects ship in 6 to 12 weeks.

By Christian Vismara

WHAT YOU GET

Everything in the box.

Solution scoped to your data

Not a template. We design the architecture around your data shape, your throughput, and your compliance constraints.

Vendor-agnostic build

You can swap Claude for GPT-4 or open-source without rewriting your app. We build with abstraction baked in.

Production-ready code

Tested, documented, observable. Code that survives the first user, not just the demo.

Compliance-aware patterns

GDPR, SOC 2, HIPAA-aware architecture if you need it. Data residency, encryption, audit trails.

Documented decisions

Architecture diagrams, ADRs, prompt versioning. So your team understands why, not just what.

Knowledge transfer

We pair with your engineers during build, not just at handover. By month two they know the system as well as we do.

THE PROCESS

How we build it.

1

Discover

1 to 2 weeks. Free if you go forward. We map data, constraints, and the success metric that actually matters.

2

Architect

One week. Stack decisions, agent or RAG or app, data flow, deployment target. You sign off on a doc.

3

Build

4 to 10 weeks depending on scope. Weekly demos against real data. We show breakage too, not just wins.

4

Deploy + tune

Two-week tuning window after first deploy. Real users hit edge cases prompts and tests cannot.

STACK

Tools we use.

Claude (Anthropic)GPT-4o (OpenAI)Llama 3 / Mistral (open-source)LangGraphLlamaIndexPinecone / Weaviate / pgvectorSupabaseAWS / GCP / AzureVercel
PRICING

Project-based, fixed price where possible.

Custom AI projects typically land between $20,000 and $150,000 depending on complexity, integrations, and compliance requirements. We quote fixed-price for well-scoped work, time-and-materials for genuinely exploratory R&D.

Discovery is free if you decide to go forward. We don't do free pitches for fully-scoped solutions, but we do help you scope.

FAQ

Common questions.

Build custom when your data is unusual, your workflow is unusual, or your compliance is unusual. Use a platform when your problem looks like the platform's landing page. Most companies overestimate how custom their problem is. We tell you up front if a platform would do.
No. We build on Claude and GPT-4 most often because they're the strongest, but we also ship on open-source (Llama 3, Mistral, Mixtral) when cost, latency, or data residency matters. We pick per project, not by ideology.
Yes, on open-source. We deploy on Together, Replicate, your AWS, or on-prem if you have the hardware. For closed models we set up the secure cloud option (Bedrock for Claude, Azure for GPT, Vertex for Gemini).
Data minimization at the prompt layer (we don't send what we don't need). Per-project DPA. SOC 2 and HIPAA-aware architecture available. Logs scrubbed of PII by default. We never train on your data and we sign agreements that say so.
They will. We scope week-by-week, not all up-front, exactly because requirements change. Small changes within scope: included. Large changes: re-scope, re-quote. Transparent and on the table, not hidden in change orders.
FREE SCOPING CALL

Got a custom problem?

30 minutes. We tell you if custom is worth it, or if a platform would do.

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How Much Does It Cost?

Honest pricing for custom AI development.