All services
4–8 weeks
AI & RAG Systems
Voice agents, RAG pipelines, and LLM features that actually ship.
Real-time AI integrations grounded in your data — STT → retrieval → LLM → TTS pipelines, document understanding, and chat experiences with citations, evals, and cost controls.
What you get
- RAG pipeline with vector DB (Pinecone) and metadata filtering
- STT + TTS (Deepgram) and LLM orchestration (Groq / OpenAI)
- Chunking + embeddings (Hugging Face / OpenAI)
- Streaming responses with graceful degradation on partial failures
- Tenant / namespace isolation for multi-customer deployments
- API + minimal admin UI for ingestion and monitoring
Outcomes you can expect
- Median end-to-end latency held to a defined budget
- Answers grounded in source material with traceable citations
- A repeatable eval harness your team can run on every change
How we'll work
- 01
Scope
Identify the highest-leverage use case — voice, knowledge search, or agent.
- 02
Prototype
Working demo in week one to de-risk latency & quality.
- 03
Harden
Add evals, observability, retries, and rate limits.
- 04
Deploy
Roll out behind feature flags with monitoring.
Best for
Teams adding their first serious AI feature, or anyone who needs a voice / RAG agent done properly.
Available for freelance & internships
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