Ai Integrationv1.0.0

Build a multi-agent support system where an orchestrator delegates to specialist agents for order lookup, returns processing, and product recommendations. Uses tool calling for database access and streaming for real-time responses in a Next.js storefront.

Implement structured extraction of entities, clauses, and obligations from contracts using instructor and Pydantic models. Multi-agent reviewer validates extractions against source text before storing in a vector database for RAG-powered legal search.

Deploy a LiteLLM-based routing layer that funnels requests across Claude, GPT, and open-source models based on cost, latency, and capability. Includes fallback chains, per-tenant rate limiting, and structured output normalization across providers.

Create a Python FastAPI service where an agentic loop plans, writes, tests, and self-corrects code using parallel tool calls to a sandboxed file system and test runner. Persistent agent memory stores project conventions across sessions.

Build an evaluation pipeline that scores Claude model outputs on quality, faithfulness, and safety using rubric-based judges. Integrates regression testing into CI so prompt changes are gated before production deployment.

Deliver fixed-scope engagements helping companies embed Claude API features—structured outputs, tool calling, and multi-agent orchestration—into existing products. High-margin projects priced hourly at $75-200/hr on Upwork.

Package the skill's patterns into a domain-specific product (legal, support, sales) with agentic loops and RAG pipelines tailored to the vertical. Charge subscription tiers based on usage and seats.

Offer a managed multi-provider routing layer with evals, cost tracking, and prompt management so engineering teams can ship AI features faster. Usage-based pricing scales with request volume.