AI & ML

Anthropic

Claude models combine long-context reasoning, tool use, and constitutional AI safety. Built for enterprise workflows where accuracy and auditability matter.

Trusted by leading organisations

United NationsSwiss GovernmentProspaIAGQantasEYANZ
The landscape

AI built around safety by design

Anthropic trains Claude using constitutional AI, producing models that are helpful, harmless, and honest without relying solely on human feedback.

Claude supports extended thinking for complex reasoning, structured tool use for API interactions, and prompt caching for cost-efficient production workloads. 200K+ token context windows process entire codebases or legal documents in a single request.

Technology snapshot

Market demand 5/5

Current industry demand for this technology

Adoption 3/5

How widely used by development teams worldwide

Scalability 4/5

How well it handles growth in load and complexity

At a glance

Models Claude Opus, Sonnet, Haiku tiers
Key features Tool use, 200K context, extended thinking
Safety Constitutional AI, built-in guardrails
Typical pattern Document processing, code review, agents
Common use cases
Document ProcessingCode ReviewAI AgentsCustomer Support
What we deliver

Our Anthropic capabilities

01

Claude API & tool use

Multi-turn conversation, structured tool calling, JSON mode, and streaming for production workflows.

Messages APITool useStreaming
02

Long-context processing

200K token contexts for entire codebases, legal documents, or financial reports without chunking.

200K contextDocument analysisRAG
03

Prompt caching & cost efficiency

Up to 90% cost reduction for repeated system prompts. Route by complexity across Opus, Sonnet, and Haiku.

Prompt cachingBatch APIModel routing
Why Adaca

Why Adaca for Anthropic?

Regulated deployment

Claude in APRA-regulated banking and healthcare with audit logging and PII redaction.

Deep Claude API experience

Extended thinking, tool use, prompt caching, and Batch API for structured multi-step workflows.

RAG for accuracy

Retrieval-augmented generation with vector stores, reranking, and citation extraction.

Production observability

Token counts, latency, tool invocations, and quality metrics traced for every call.

Full-stack AI teams

Next.js front-ends, Python orchestration, vector databases, and CI/CD. One team from prompt to production.

Multi-model evaluation

Benchmarking Claude against GPT-4 and Gemini on actual use cases with structured evaluation.

Building with Claude?

Talk to our AI team about Claude integration, RAG pipeline design, or regulated deployment.

Talk to Our Experts