15+
Claude Integrations Shipped
🤖AI Engineering
Claude Application Development
We build production applications powered by Anthropic's Claude — document analysis over 1M-token contexts with Opus 4.6, agentic workflows with tool use and MCP servers, multi-modal pipelines processing text and images together, and streaming AI features for SaaS products. Not wrapper chatbots — real integrations that handle business complexity.
From structured extraction over 1M-token legal archives to agentic tool-use workflows with Opus 4.6 that call your internal APIs — we architect Claude applications that handle real business complexity, not demo-day parlor tricks.
- Full Anthropic API expertise — not just basic completions
- MCP servers connecting Claude to your internal tools
- Production cost optimization with model routing
Share your scope and get a tailored estimate in 48 hours.
Proposal in 48 hours
NDA-ready engagement
Weekly sprint demos
1M
Context Window Tokens
50%
Lower Cost vs GPT-4o
<1s
Streaming First Token
The Problem
Where Teams Get Stuck Without Claude Expertise
These are the real blockers we hear from CTOs and engineering leads before they reach out.
Your team built a ChatGPT wrapper, but it hallucinates on edge cases and can't call your internal tools. Now the CEO is asking why the AI demo from 3 months ago still isn't in production.
You're manually chunking documents to fit context windows, losing information at chunk boundaries, and spending more time on prompt engineering than actual product work. Claude's 1M-token context solves this — but only if you architect it right.
Claude's API looks simple in the docs, but streaming error handling, structured output parsing, extended thinking, and cost management at scale are engineering problems your team hasn't solved before.
You evaluated Claude Opus 4.6 vs GPT-4o vs open-source models, but the comparison spreadsheet keeps growing and nobody is confident enough to commit engineering resources to one platform.
The Outcome
Results You Can Present to Stakeholders
What changes after we ship — measurable outcomes, not marketing promises.
Production Claude integration processing real customer data — not a demo that only works on cherry-picked examples.
40-60% lower API costs through model routing (Opus 4.6 for complex reasoning, Haiku 4.5 for simple tasks) and prompt caching.
MCP servers connecting Claude to your CRM, database, and internal tools — turning it from a text generator into a workflow engine.
Streaming architecture with sub-1s first-token latency, proper error handling, and rate limit management for production traffic.
What We Build
Business Use Cases for Claude
Production systems we've shipped — not hypothetical demos or POCs that never go live.
01
SaaS AI Features
Embed Claude into your product — search, summarization, content generation, and intelligent workflows your users interact with daily.
02
Document Intelligence
Process contracts, invoices, research papers, and compliance documents at scale using Claude's 1M-token context window — entire codebases and legal archives in a single pass.
03
Developer Tools
Code review assistants, documentation generators, test writers, and debugging tools powered by Claude's strong code understanding.
04
Customer Service Agents
Agentic customer support that reads your knowledge base, queries your CRM, and resolves tickets — with human escalation for edge cases.
Scope of Work
What We Deliver
Concrete outputs from each engagement — architecture docs, working code, deployed infrastructure.
API Architecture
Model selection, prompt engineering, token budget modeling, streaming design, and integration architecture.
Tool Use Integration
Function calling schemas, MCP server development, structured output pipelines, and error handling.
Multi-Modal Pipeline
Combined text-vision workflows, document analysis, image processing, and extraction pipelines.
Production Deployment
Streaming infrastructure, cost monitoring, rate limiting, caching, and auto-scaling.
Why Us
Why Teams Choose Cartoon Mango for Claude
15+ Claude Integrations Shipped
We've built production Claude applications for document processing, customer service, code review, and internal knowledge bases. Your project isn't our first.
Full API Surface Expertise
Messages API, Streaming, Tool Use, Computer Use, Batch API, MCP servers — not just basic completions. We use the right Claude capability for each problem.
Cost-Optimized from Day One
Model routing between Opus 4.6, Sonnet 4.6, and Haiku 4.5 based on task complexity. Prompt caching, Batch API for async workloads, and token budget alerts. We typically save 40-60% vs teams that call Opus for everything.
Sprint-Based, Not Agency-Style
Weekly demos, PRs to your repo, Slack communication. We integrate into your engineering org, not deliver a PDF at the end of 3 months.
Our Process
How We Execute
Sprint-based delivery with weekly demos — no disappearing for 3 months.
1
Discovery
Map your use case to Claude's capabilities. Model selection (Opus 4.6 / Sonnet 4.6 / Haiku 4.5), token economics, and feasibility validation.
2
Architecture
Design the integration — API layer, prompt templates, tool schemas, MCP servers, and data flow.
3
Build
Implement with streaming, error handling, structured outputs, and comprehensive evaluation suites.
4
Scale
Production deployment with cost monitoring, model routing, caching, and performance optimization.
Explore More
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Need a delivery-ready architecture for Claude?
Share your scope and constraints. We'll propose a practical architecture, timeline, and sprint plan your team can execute with confidence.
Common Questions
FAQs About Claude Development
Real answers to what buyers actually search before hiring a Claude team.
Opus 4.6 is the most capable model — best for complex reasoning, long-document analysis, and agentic workflows over 1M-token contexts. Sonnet 4.6 balances quality and speed for most production use cases. Haiku 4.5 is the fastest and cheapest — ideal for classification, simple extraction, and high-volume tasks where sub-100ms latency matters.
