AI Services
Explore Sigi Technologies AI services — generative AI, agents, RAG assistants, custom ML, LLM optimization, and integration. Start with the capability that fits your product, or combine them into a larger build.
Recognized & reviewed on
Each area is a focused, production-oriented service. Start where the business value is clearest, or combine them into a larger build.
End-to-end AI features built into your product, from scoping to production and monitoring.
Autonomous agents and multi-step workflows with clear ownership, guardrails, and evaluation.
GenAI features grounded in real product constraints — not demos that never ship.
Private retrieval-augmented assistants over your own documents and data, with cost and latency control.
Trained, evaluated, and production-operated machine learning your team can measure.
Cost, latency, safety, and quality controls so LLM systems stay reliable at scale.
Wire AI into your existing systems, tools, and workflows without destabilizing the core.
Practical AI guides from the Sigi team on chatbots, retrieval, agents, and model cost.
Guide > AI
What is RAG in AI? A researcher explains retrieval-augmented generation: how it works, its architecture, how to evaluate it, and the cases where you should not use it.
Guide > AI
Building an AI chatbot for business: chatbot versus agent, retrieval, evaluation, and human handoff — capability framing until Sigi publishes a named AI case study.
Guide > AI
AI agent use cases judged against published benchmark numbers instead of vendor claims: what agents complete reliably, where they break, and how to scope a first pilot.
Guide > AI
LLM cost optimization with sourced numbers: prompt caching multipliers, model routing, batch discounts, quantization, self-hosting economics and evaluation as the lever that makes the rest safe.
You can start with a discovery sprint to validate feasibility and ROI, a prototype-to-MVP build, or ongoing optimization after launch. Each capability can be delivered on its own or combined into a larger build.
Discovery is usually a week or two; a production-ready feature typically takes longer depending on data readiness and integration needs. We scope timelines against your specific use case.
You own the code, the resulting solution, and your data. We apply access boundaries and can sign an NDA before reviewing sensitive information.
We use grounded retrieval where appropriate, structured outputs, evaluation sets, and guardrails matched to your workflow’s risk level.
Yes. We integrate AI into your current app and collaborate with your internal engineering team.
Hire vetted AI engineers who work in your codebase and ship in your sprint cadence, or engage Sigi to deliver the full build.
