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Anthropic

Claude — the world's leading AI model.

Claude is the AI model we use ourselves. It is the model behind AISA. It is the model we recommend to most clients as the primary platform for serious work — code, analysis, regulated decision-making, agentic action. We deploy Claude.ai for Enterprise, Claude Code for engineering teams, custom MCP servers, and Anthropic API integrations.

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Why Claude — what makes it different

Claude is consistently rated the world's leading frontier AI model on the dimensions that matter for serious work: reasoning depth, instruction-following, code quality, honesty about uncertainty, and steerability. Anthropic's design philosophy — "be helpful, harmless, and honest" — produces an AI that admits when it does not know, asks clarifying questions when the prompt is ambiguous, and refuses confidently-wrong answers. For regulated industries, code-heavy teams, and high-stakes decisions, this is the difference between an AI that helps and an AI that creates downstream cleanup.

What we deliver

Claude rollout, end to end.

Claude.ai for Enterprise

The chat product for everyone: SSO with your identity provider, MFA enforced, retention controls, custom system prompts (Projects), workspace governance, audit logging. Per-seat licensing through Anthropic.

Claude Code for engineering teams

The agentic AI command-line + IDE assistant for engineers. Multi-file refactors, test generation, code review, documentation. Hooks into your existing repo + CI. We deploy with sandboxing rules tuned to your environment and audit logging into your SIEM.

Custom MCP servers

MCP (Model Context Protocol) is how Claude reaches your internal systems — your CRM, your ticket queue, your knowledge base, your wiki, your databases. We design and deploy MCP servers that give Claude the right tool surface for your work, with scoped permissions and audit logging.

Anthropic API integrations

For custom workloads — internal apps, customer-facing AI, batch document processing — we build on the Anthropic API. Production patterns include prompt caching for cost control, streaming for latency, structured output for reliable parsing, and tool use for agentic workflows.

Cost + usage governance

Per-team budgets, rate limits, model-tier routing (Opus for hard problems, Sonnet for steady-state, Haiku for high-volume), prompt-caching to reduce costs by up to 90%. Monthly review of usage vs. budget with optimization recommendations.

Adoption + training

Role-by-role training: founders, engineers, sales, support, finance, ops. Each role gets a 90-minute session focused on the specific patterns that move the needle for their work — not generic "what is AI" content.

Who Claude is best for

Where Claude wins, where it does not.

Where Claude wins

  • Code-heavy teams (Claude Code is the leading agentic coding product)
  • Regulated industries (Anthropic's safety focus aligns with audit + compliance)
  • Long, complex documents (1M-token context window — entire contracts, codebases)
  • Honest reasoning (Claude flags uncertainty, asks clarifying questions)
  • Tool use + agentic workflows (MCP is the open standard, Claude is the reference)
  • Customer-facing AI where confident-wrong answers would be costly

Where Claude is NOT the answer

  • Image generation (use ChatGPT / DALL·E or Gemini)
  • Workspace-native productivity (use Gemini for Workspace)
  • Voice / video real-time (use ChatGPT advanced voice or Gemini Live)
  • Maximum-breadth ecosystem integrations (ChatGPT has the largest)

Education

What Claude buyers should understand.

The Opus / Sonnet / Haiku model family — and how to use it

Anthropic publishes three model tiers. Opus: highest intelligence, slower, most expensive — best for hard reasoning and one-shot work where quality matters more than cost. Sonnet: the production workhorse — strong reasoning, faster, much cheaper — best for steady-state production workloads. Haiku: smallest + fastest + cheapest — best for high-volume classification, simple lookups, and chained workflows where each step is constrained. Real rollouts use all three with routing rules.

Why prompt caching is a game-changer

Most production AI workloads send the same context (a system prompt, a knowledge base, a customer profile) on every request. Prompt caching tells Anthropic "this part is reusable" — and reduces the cost of that part by ~90% on every cache-hit request. Real production deployments routinely cut Anthropic API spend by 60–80% by adopting prompt caching properly.

What MCP actually is, and why it matters

MCP (Model Context Protocol) is the open standard for connecting AI to tools. Before MCP, every AI integration was custom — different protocol per AI vendor, fragile, vendor-locked. With MCP, you build a tool server once and it works with any MCP-compatible AI (Claude, plus anyone else who adopts the standard). MCP is what lets Claude reach your QuickBooks, your Salesforce, your custom internal API, your company knowledge base — with one consistent permission + audit model.

Why Claude Code is different from "AI in your IDE"

Most AI-in-IDE products are autocomplete on steroids. Claude Code is an agent that can read your repo, plan a multi-file change, write the code, run the tests, fix the failures, and submit a PR — all while you are doing other work. The shape of engineering changes when an agent can take work end-to-end, not just suggest the next line. We deploy with sandboxing tuned to your environment so Claude Code cannot do anything you have not authorized.

Ready to make Claude your team's AI?

Tell us your team size, the work you want AI to take over, and your timeline. We will come back with a written plan + quote within five business days.

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