Claude Opus, Sonnet, or Haiku?

Opus for heaviest reasoning. Sonnet for most production work (best quality per dollar). Haiku for high-volume classification where speed and cost matter more than peak quality. Most production apps mix all three.

Tool use vs function calling?

Claude's tool_use protocol is cleaner for multi-step agents (stateful across tool calls). OpenAI function calling is simpler for single-shot tool invocation. Use Claude when agents chain many tool calls.

Yes. The RAG pipeline (ingestion, embedding, retrieval, re-ranking) wires into Claude the same way it wires into OpenAI. Claude's long context means you can often send more retrieved chunks without re-ranking.

Can you migrate from OpenAI to Claude?

Yes. The prompt-plus-validation layer abstracts the model. Migration is re-running the eval harness against Claude and tuning prompts for Claude-specific patterns. Typical migration 2 to 4 weeks.

Claude AI integration delivery

Claude AI integration services — long context, tool use, MCP

Wired into product with guardrails and cost caps. Prompt caching for 60 to 90% savings. MCP Protocol proven in production.

Available for new projects

See AI Automation

Starting at $3,000/mo · monthly retainer

Who this is for

Company that picked Claude over GPT for long-context, MCP-compatible workflows, or agent-style tooling.

The pain today

Few shops have shipped Claude-specific features (tool use, MCP, long docs) at production quality.
Prompt caching is theoretical on your team — you pay full price for every call.
Claude's tool-use protocol is different from OpenAI's function calling.
MCP is the future but nobody on the team has shipped it.

The outcome you get

Claude integrations wired into product — long-context document triage, agentic tools, MCP servers.
Prompt caching delivering 60 to 90% cost reduction on repetitive prompts.
Tool use with structured state across multi-step agents.
MCP servers exposing your APIs to Claude Code, Cursor, and any MCP client.

What Claude integration work covers

Claude AI engagements cover: Anthropic API integration with the TypeScript or Python SDK, prompt design (system prompts plus prompt caching plus versioning), tool use (multi-step agents with structured tool_use plus tool_result protocol), long-context processing (200k context window with prompt caching for repeated base prompts), MCP server authoring (when exposing APIs to Claude Code or Cursor), cost monitoring (token counts per feature, budget alerts), eval harness (test set of inputs plus expected outputs, run on every prompt change), and observability (structured logs of prompts plus completions).

Instill — Claude + MCP in production

Instill (SITE-FACTS §6) runs Next.js 16 plus React 19 plus TypeScript plus PostgreSQL plus Vercel plus MCP Protocol. 30+ active users, 1,000+ skills saved, 45+ projects powered. MCP Protocol ships an open standard MCP server so Instill skills work inside Claude Code, Cursor, and any MCP client. Not a side project — a live AI product with real users. The Claude patterns used there (prompt caching, tool use, MCP) transfer directly to Claude-in-your-product engagements.

Prompt caching — the cost lever most teams miss

Anthropic's prompt caching (available since 2024) stores the static part of long prompts server-side and charges a fraction for cache reads. Typical savings: 60 to 90% on prompts with 5000+ tokens of static context (system prompt plus RAG-retrieved documents plus tool definitions). Most Claude implementations do not use it because the team does not know the flag exists or does not structure prompts for cache-friendly reuse. Every Claude engagement I run turns on prompt caching on day one — the cost impact is immediate.

Pricing and scope

AI Automation retainer at $3,000 per month. 2 to 4 day delivery cycles. 14-day money-back. Cancel anytime. Typical Claude integration engagement runs 6 to 12 weeks for a focused use case (document triage, agentic assistant, MCP server) plus ongoing retainer maintenance.

Recent proof

A comparable engagement, delivered and documented.

AI Product · Beta

A prompt library that works with every AI tool

A home for your best AI prompts. Save them once, then use them in Claude, Cursor, or any AI tool you work with. No more copy-paste.

AI Product30+ active usersCross-tool workflowsSelf-funded

Read the case study

Frequently asked questions

The questions prospects ask before they book.

Claude Opus, Sonnet, or Haiku?: Opus for heaviest reasoning. Sonnet for most production work (best quality per dollar). Haiku for high-volume classification where speed and cost matter more than peak quality. Most production apps mix all three.
Tool use vs function calling?: Claude's tool_use protocol is cleaner for multi-step agents (stateful across tool calls). OpenAI function calling is simpler for single-shot tool invocation. Use Claude when agents chain many tool calls.
MCP server authoring?: Yes. Proven at Instill. MCP server plus tool registration plus auth plus client compatibility — I ship it.
Claude plus RAG?: Yes. The RAG pipeline (ingestion, embedding, retrieval, re-ranking) wires into Claude the same way it wires into OpenAI. Claude's long context means you can often send more retrieved chunks without re-ranking.
Can you migrate from OpenAI to Claude?: Yes. The prompt-plus-validation layer abstracts the model. Migration is re-running the eval harness against Claude and tuning prompts for Claude-specific patterns. Typical migration 2 to 4 weeks.

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Available for new projects