Technology
Anthropic Claude Development — Long-Context, Tool-Use & Computer Use
Production builds on Claude Opus, Sonnet, and Haiku — long-context reasoning, tool use, prompt caching, and Computer Use agents.
What we build with Anthropic (Claude)
- Claude Opus, Sonnet, and Haiku integration with cost-aware routing
- Tool use, multi-step agents, and Computer Use automation
- Prompt caching to cut latency and token cost on repeated context
- Long-context reasoning over contracts, codebases, and case files
- Constitutional-AI-aligned guardrails for regulated industries
- Streaming, structured output, and JSON-schema-validated responses
Why DiveScale
Built by engineers who ship Anthropic (Claude) in production
Anthropic’s Claude models are our default choice for long-context reasoning, code generation, and agentic workflows where output reliability matters. DiveScale has shipped Claude into customer-facing copilots, internal review agents, and document-heavy back-office automations.
We design around Claude’s strengths: extended thinking for hard reasoning, prompt caching to amortize big system prompts, and tool use for agents that take real actions. Each integration ships with evals tuned to your data — not generic benchmarks.
Operationally we cover retries, fallback to alternative models, observability, prompt versioning, and the security posture (zero data retention, audit logs) regulated industries need from day one.
Anthropic (Claude) use cases we deliver
How we deliver
Our Anthropic (Claude) delivery process
- 01
Model + workflow design
We pick the right Claude tier (Opus, Sonnet, Haiku), and design the prompt, tool surface, and evaluation harness around your task.
- 02
Prototype with prompt caching
We architect prompts so cacheable context (system, schema, examples) is reused — typically cutting per-call cost 50–80%.
- 03
Hardening & evals
Golden datasets, automated regressions, guardrails, structured-output validation, and fallback model wiring.
- 04
Operate & evolve
We monitor quality drift across model versions, tune prompts, and stay on as Anthropic ships new models.
Related technologies
OpenAI
Production-grade integrations with GPT-4o, GPT-4.1, o-series reasoning models, Realtime voice, embeddings, and the Assistants API.
Learn moreLLMs
Production LLM engineering — model selection, RAG, fine-tuning, evals, guardrails, and the operational layer that keeps quality high.
Learn moreAgentic Workflows
Multi-step AI agents that plan, call tools, write to systems, and stay inside policy — with human-in-the-loop checkpoints where it matters.
Learn morePython
Production Python engineering — FastAPI services, async pipelines, AI/ML workloads, data engineering at scale, and the typed, tested, observable discipline production Python deserves.
Learn moreAnthropic (Claude) — Frequently Asked Questions
Claude tends to win on long context, code reasoning, careful refusal behavior, and tool-use reliability. We benchmark both on your data before recommending — and abstract the provider so you can switch without rewriting code.
