AstraneoTechSolve it with AI or cloud, safely, and without runaway cost.
AstraneoTech takes on AI and cloud work as a standalone service, separate from the chief-architect-for-hire offering. We build AI that can reason, generate content, or automate repetitive work that's eating your team's time. At RR Ventures, AI automation removed roughly 40% of manual tasks. We design cloud setups that stay fast as you grow while cutting waste. At INODE RAMS we reduced cloud cost by 30% and cut wasted billing time by over 50%. Every AI system we build has safety limits designed in: the Diagnopedia medical chatbot gives helpful information but never attempts a diagnosis, by design. Designed by a senior engineer, scoped to your problem, delivered worldwide.
What kind of AI can you build?
AI that reasons, generates, or automates, built to solve a real problem, not to demo.
AI that can reason, generate content, or automate repetitive work that is eating your team's time. At RR Ventures, AI automation removed roughly 40% of manual tasks.
Will the AI behave safely?
Safety limits are part of the plan, not an afterthought.
The Diagnopedia medical chatbot gives helpful information but never attempts a diagnosis, by design. Safety limits are written into the specification from the start.
Can you cut our cloud bill?
Usually, yes, by fixing the setup, not just trimming.
At INODE RAMS we reduced AWS cost by 30% and cut wasted billing time by over 50% by fixing the architecture and adding scheduled resource management.
Is this the same as the part-time CTO service?
No, this is hands-on building, scoped to one project.
AI and cloud engineering is a standalone build service, separate from the fractional CTO leadership engagement.
Common questions about AI and cloud engineering
Clear answers.
- Are you tied to a specific LLM or cloud provider?
- No. Model and provider choices are made per problem. The Diagnopedia chatbot, for instance, uses retrieval-augmented generation on OpenAI; another build may use a different provider where it fits better.
- How is our data handled and kept private?
- Data handling is designed against HIPAA, GDPR, and the DPDP Act where they apply. Systems can be built so that sensitive data stays inside infrastructure you own.
- Who owns the model and the infrastructure?
- You do. The build, its configuration, and the infrastructure are client-owned, as with the Diagnopedia chatbot, deployed on infrastructure fully owned by the client.
- Grounded answers from your content, or a trained model?
- Whichever the problem calls for. Answers grounded in your own approved content (what Diagnopedia uses) are often the lower-risk, lower-cost path and are recommended only where they actually fit.
- Can you control the cost?
- Cost is an architecture decision first and a FinOps practice second. At INODE RAMS this produced a 30% AWS cost reduction and a 50%-plus cut in idle billing.
- How do you keep AI systems safe?
- Guardrails are written into the specification. Diagnopedia is the reference case: it informs without attempting diagnosis, by design.
- Can it run on our own infrastructure?
- Yes. Hosting on client-owned infrastructure is the default, not an exception.
- How do we start?
- Describe the AI or cloud problem and your constraints via the contact page. You get a direct, technical response from the person who would architect it.