Bridging
the gap.
The AI market does not wait
Every week the AI market ships a new model, framework or product. Most do not survive six months. The hard part is not adopting AI. It is knowing what is worth it for your business.
Research, architecture, development
One process, from studying the case to the system running.
Research
Market readingWe follow AI technology daily. We filter what makes sense for your business, not what is hype. And we measure which stack fits your case before settling the decision.
Architecture
Strategy and solution designWe design the strategy and the architecture of the solution from the research and your context: model, stack, cost and implementation plan.
Development
Build and deliveryWe build the product and take it inside your company. In-house development, from start to delivery.
What we build
Six systems that come up most often in projects.
Agent harness
Order triage, ticket creation, proposal checks. It is the environment the agent runs in: it reads your systems, decides and acts, with a human approval point wherever you want one and a record of what was done.
Document workflow
Invoices, contracts, reports and bills someone types in by hand today. The file goes in, checked data comes out, and it keeps working when the supplier changes the layout.
Internal assistant with RAG
The question someone has to hunt for in a folder, a spreadsheet or a contract. The assistant searches the company's own data and answers in plain language, with the source passage attached.
MCP server
It is what gives the AI access to what already runs in the company. Wired to the ERP, the CRM and internal tools, it starts seeing orders, customers, stock and history, and acting on them, without replacing any system.
Model evaluation bench
Before you scale, we run the candidate models on your data and show what each completed task costs and how many come out right. You decide on numbers, not on a demo.
Research and reporting pipeline
The document someone compiles by hand every week: market research, competitor summaries, internal briefings. Agents gather, cross-check against company context and deliver it finished.
Published research
AI Radar · Daily · August 29, 2026
AI Radar · Daily · August 28, 2026
All reports →Open source
Context engineering toolkit for AI applications. Token-aware pipelines, hybrid retrieval and provider-agnostic formatting.
Hands-on Jupyter Notebook recipes for the Anchor context engineering toolkit
Agent skills for building AI applications with anchor, the context engineering toolkit
Astro on GitHub →Direct questions
What exactly does Astro do?
Development. We study the case, measure which stack fits, design the architecture and build the system, from start to delivery.
Who works on the project?
Astro has its own team. Development is in-house, with no third-party teams.
How does it start?
With a conversation about your context. From there we say what can be built, or we say if AI does not solve your case.
Not sure where to start?
Get in touchTalk to us
Tell us about your project or challenge. We reply within 24 hours.
Or reach us directly
contact@astrointelligence.dev