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AI / LLM
Anthropic Claude
Long-context document processing and safety-critical AI applications
200KToken context window
3×Cheaper than GPT-4 (Haiku)
99.95%API uptime SLA
5Safety layers built-in
HOW WE USE IT
Anthropic Claude in our stack
We build applications with Anthropic's Claude models — known for their 200K token context window, constitutional AI safety, and strong reasoning capabilities. Ideal for document-heavy workflows, compliance-sensitive applications, and long-form analysis.
CAPABILITIES
What we deliver
- Claude 3 (Haiku, Sonnet, Opus) API integration
- 200K token context for long-document workflows
- Constitutional AI for compliance-sensitive apps
- Prompt caching for cost reduction
- Tool use and function calling
- Claude as a reasoning engine in multi-agent systems
USE CASES
How we apply Claude
Legal Document Analysis
Process entire contracts, case files, and regulatory documents in a single context window with Claude Opus.
Safety-Critical AI
Applications requiring explainable, auditable AI decisions — Claude's constitutional training reduces harmful outputs.
Research & Synthesis
Long-form research synthesis from multiple documents, academic papers, or technical specifications.
Engineering Stack
Built with the tools that matter
38 production-grade technologies — every one battle-tested in shipped products.
Frequently Asked Questions
Didn't find what you were searching for? Reach out to us at [email protected] and we'll assist you promptly.
Claude has three specific advantages: its 200K token context window handles entire documents and large codebases in a single request; its constitutional AI training produces fewer harmful outputs in safety-sensitive applications; and Claude Haiku delivers strong performance at lower cost for high-throughput tasks. We recommend Claude for legal document analysis, compliance-sensitive applications, long-form research synthesis, and use cases where GPT-4 produces outputs that require more guardrails.
Production Claude deployments typically include: prompt caching to reduce cost on repeated context, streaming responses for real-time UX, structured output enforcement with tool use, context window management for multi-turn conversations, and a fallback chain to GPT-4 or Claude Haiku for different cost and performance tiers. We build evaluation frameworks measuring accuracy, latency, and context utilization to ensure production performance matches development benchmarks.
Basic Claude API integrations take 2-4 weeks including evaluation and deployment. Long-document processing pipelines (legal, compliance, research) with structured output handling typically take 4-8 weeks. Complex multi-agent architectures using Claude as a reasoning engine run 6-10 weeks depending on tool complexity and evaluation rigor required.
FROM OUR CLIENTS
Built with teams who ship
The team took our AI concept from whiteboard to production in 10 weeks. The architecture they designed handles 10x our expected load with no issues.
Insights
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GET STARTED
Want to use Claude in your project?
Talk to an engineer about your requirements. Proposal within 48 hours.