We build
anything AI.

From agentic workflows to custom ML models. Dianotic turns your most complex challenges into production-ready intelligence.

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01 — capabilities

Three lines of expertise, one team.

/01

Intelligent systems

We design and deploy AI that acts: agent pipelines, conversational assistants, and custom projects that run autonomously and self-correct.

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/02

Data & models

We build ML models and RAG systems trained on your data, tuned to your exact problem, and ready for production from day one.

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/03

Strategy & training

We help you understand where AI creates the most value, choose the right tools, and train your team to use them effectively.

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02 — method

The arc, diagrammed.

/01 DISCOVERY

Analyse the gap

We start with your challenge. What are you solving? What does your stack look like? A focused gap analysis surfaces the highest-value opportunities.

/02 SCOPE

Fix the price

Within 48 hours: a written proposal with architecture, timeline, and fixed cost. No hourly billing, no vague estimates.

/03 BUILD

Ship in cycles

Iterative two-week sprints. You see working demos, give feedback, and stay in the loop at every stage.

/04 DELIVER

Deploy and transfer

We ship to production, document everything, and hand over complete ownership. Ongoing support is available if you need it.

“AI that cannot explain its reasoning is not ready for production.”

— Dianotic principle
04 — delivery

An interface for results.

What a Dianotic engagement delivers

Every project ships working software, fully documented and production-ready. You get complete ownership of the code, the models, and the infrastructure from day one.

Built for teams who need their AI to be reliable, explainable, and maintainable long after the engagement ends.

  • 01Production-ready code with full documentation
  • 02Deployed and tested on your infrastructure
  • 03Complete knowledge transfer and training
  • 04Post-launch support and monitoring
dianotic · engagement
// discovery → scope → build → deliver

▸ dianotic engage --service rag --scope defined

[discovery] gap analysis complete ✓
↳ "Internal docs scattered across 4 systems"

[scope] proposal sent within 48h ✓
↳ RAG system, 6-week timeline, fixed price

[build]
↳ sprint 1: ingestion pipeline + vector store
↳ sprint 2: retrieval + citation engine
↳ sprint 3: UI + auth + deploy

[deliver] ✓ deployed · docs transferred · support active

▸
03 — evidence

What working with us looks like.

Proposal turnaround<48hFrom discovery call to written proposal with architecture, timeline, and fixed price.
To production4-16wkFocused chatbot in 4 weeks. Multi-agent system in 16. Scoped precisely before work begins.
Service areas7From agentic workflows to AI training. One team, full coverage.
Code ownership100%All code, models, and infrastructure belong to you from day one.
Hourly bills0Fixed-price for defined scopes. Retainer for ongoing work. No billing surprises.
Δ ARCThe arc of reasoning: every engagement follows the same disciplined path from discovery to delivery.

Tell us what you are building.

A 30-minute discovery call. We listen, we ask the right questions, and within 48 hours you have a plan.

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