Agency · AnthropicFree audit

ANTHROPIC AGENCY FOR CLAUDE-POWERED PRODUCTS THAT SHIP

Hack'celeration is an Anthropic agency that builds production-grade Claude API integrations. The team ships chatbots, long-document pipelines, agentic workflows, prompt caching and private fine-tunes on Claude Sonnet 4.5 and Opus 4.7. Average latency cut by 41% via prompt caching, with token costs down 65% across most use cases.

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Anthropic Agency — workflow & automation.
Hack'celeration Agency

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Our agency · why us

Why pick an Anthropic agency that builds for prod

Claude is the model of choice when you care about reasoning quality, long context and lower hallucination rates. Hack'celeration has shipped 35+ Anthropic API integrations in 2025, on AWS Bedrock, Google Vertex and direct Anthropic API. The team knows the gotchas: tool use loops, prompt caching gotchas with system prompts, 200k context cost spirals, MCP server design, structured output reliability.

What you get: working Claude integrations, not slide decks. Production code, retries, fallbacks, logs, observability via Langfuse or Helicone, and a runbook your team can read. A field note: 8 out of 10 Claude integrations the team audits do not use prompt caching, which leaves 50 to 90% of token cost on the table on long system prompts. Fixing it is a 30 minute job. Crosslinks: AI agency, AI agent agency, Claude Code agency, OpenAI agency for multi-provider routing.

Anthropic · agency services

What the team delivers on the Anthropic stack

Claude API integration. Working integrations across the Anthropic SDK (Python, Node, TypeScript), AWS Bedrock and Google Vertex. Auth via API key or AWS SigV4, region selection (us-east-1, eu-central-1 for EU data residency), retries with exponential backoff, structured logging. The team picks Sonnet 4.5 for speed and cost, Opus 4.7 for reasoning-heavy tasks, Haiku for high-volume cheap calls.

Long context and prompt caching. Claude's 200k token context window unlocks long-document use cases (contracts, manuals, research papers). The team designs caching strategies that hit 90%+ cache rates on system prompts and reference docs, cutting cost by up to 90% on repeated queries. Quick win: cache your 8k token system prompt and your team's top 20 reference documents. Saves 40 to 70% of monthly Anthropic bill.

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Tool use and agents. Claude's tool use API is the cleanest of any model. The team designs tool schemas, handles parallel tool calls, manages tool-use loops with proper termination, and ships agents that call into your internal APIs (CRM, ticketing, ERP). MCP (Model Context Protocol) servers built in-house for reusable tool catalogs across agents. Crosslink: AI agent agency.

RAG and private fine-tunes. RAG pipelines on Pinecone, Weaviate, Qdrant or pgvector, with chunking strategies tuned per document type. The team also runs prompt-based fine-tuning patterns (few-shot, chain-of-thought) and integrates with Claude's batch API for offline scoring at 50% cost. Real fine-tuning weights are not yet public on Claude; the team uses Anthropic's prompt customization features and recommends fallback to fine-tuned open models (Llama, Mistral) when true fine-tuning is required.

-90%
TOKENS
on repeated calls via prompt caching
-41%
LATENCY
average p95 latency drop on caching + streaming
+35%
TASK ACCURACY
vs prior LLM on reasoning-heavy B2B tasks
Anthropic · playbook

How the team rolls Claude into prod in 5 weeks

Week 1: use-case audit and model selection. Sonnet 4.5, Opus 4.7 or Haiku depending on speed, cost and reasoning needs. Prompt engineering on 3 to 5 representative tasks. Week 2: API integration, retry logic, observability via Langfuse or Helicone, structured output testing. Week 3: prompt caching strategy, RAG pipeline if needed, batch API for offline workloads. Week 4: tool use, MCP servers for reusable tools, agent loops with termination conditions. Week 5: load testing, eval suite (Promptfoo or in-house), runbook for your team. Quick win: add Langfuse on day 1. Without observability, debugging a Claude agent in prod is guesswork.

Anthropic · multi-team

Claude API across every business team

Sales and revops. Long-context analysis of sales calls (Gong, Modjo) and CRM history. Claude summarizes 20-minute calls into account briefs, extracts next steps, scores deal health. Integrated with HubSpot and Salesforce via API. Crosslinks: HubSpot agency, Salesforce agency.

Customer support. Claude-powered ticket triage, auto-draft replies, escalation classification. Sonnet 4.5 hits 88 to 94% accuracy on intent classification across 30+ categories in the team's benchmarks. Integrated with Zendesk, Intercom, Front. Human-in-the-loop for sensitive cases.

Product and engineering. Claude Code in IDEs (Claude Code agency), code review agents, internal documentation chatbots over Confluence and Notion. The team also ships Claude-powered observability assistants that read logs and propose fixes inside Slack.

94%
ACCURACY
on Claude 4.5 ticket intent classification benchmark
-58%
AHT
support handle time after auto-draft + triage
+22%
CLOSE RATE
on sales calls with Claude-generated account briefs
Our agency · innovations

An Anthropic agency on the frontier of Claude

Claude moves fast. Sonnet 4.5 dropped in late 2024 with stronger tool use and computer use. Opus 4.7 in 2025 raised the bar on reasoning and long-context tasks. The team tracks each release and ports clients to the right model within days, not quarters. The team also runs internal benchmarks: cost per task, latency, accuracy on your specific workflows. No marketing claims, just numbers.

MCP (Model Context Protocol) is the team's preferred way to share tools across Claude agents. The team builds private MCP servers for your internal APIs (HubSpot, Salesforce, Notion, internal DBs) so every Claude agent reuses the same tool catalog. One source of truth, fewer bugs, faster iteration. Combined with Claude Code in your dev team, you can get from prototype to production in 3 to 4 weeks. Crosslink: Claude Code agency, Claude Cowork agency.

Frequently asked questions

01How much does the Claude API cost?+
Anthropic charges per million tokens. As of 2026, Claude Sonnet 4.5 is around 3 USD per million input tokens and 15 USD per million output. Opus 4.7 is around 15 USD input and 75 USD output. Haiku is the cheapest at roughly 0.80 USD input and 4 USD output. Prompt caching reduces input cost by up to 90% on cache hits. Batch API gives a 50% discount on async workloads. The team builds your cost model upfront so you know your monthly bill before going live.
02Should we use Claude API directly, Bedrock, or Vertex AI?+
Direct Anthropic API gives you the fastest model access and newest features. AWS Bedrock is the right call if your stack is on AWS and your security team needs IAM, VPC endpoints and SOC2. Google Vertex AI fits Google Cloud customers. Pricing is similar. The team picks based on your data residency needs, existing cloud, and how fast you need new model versions. For EU data residency, Bedrock in eu-central-1 is the cleanest answer today.
03How does Claude compare to GPT-4o, Gemini, and DeepSeek?+
Claude Sonnet 4.5 and Opus 4.7 lead on long-context reasoning and lower hallucination rates. GPT-4o is faster on simple chat and has stronger image generation. Gemini 2 has the longest context window (1M+) and tight Google Workspace integration. DeepSeek-V3 is dramatically cheaper but lower on safety and English nuance. The team often runs a multi-provider router so the right model handles each task. Crosslinks: OpenAI agency, Gemini agency, DeepSeek agency.
04Is Claude API GDPR-compliant for EU companies?+
Yes if configured correctly. Anthropic's direct API processes data in the US, which requires SCCs and a clear DPA. AWS Bedrock in eu-central-1 (Frankfurt) keeps Claude inference in the EU and is the cleanest path for EU GDPR. The team sets up region-locked routing, data retention policies (Anthropic does not train on API data, retention is 30 days by default), and DPIA documentation for your DPO. For health or banking data, the team adds tokenization before sending data to Claude.
05Can Claude be fine-tuned on our private data?+
True weight-based fine-tuning is not openly available on Claude as of 2026. Anthropic offers enterprise customization for select clients via Bedrock. For most needs, the team uses prompt customization (system prompts, few-shot examples, RAG) which covers 90% of practical use cases. If you need true fine-tuning, the team ships fallbacks on Llama 3 or Mistral for the specific tasks that require it. Crosslink: Llama agency, Mistral agency.
06What is MCP and why does it matter for Claude integrations?+
MCP (Model Context Protocol) is Anthropic's open protocol for connecting Claude to external tools and data sources. Think of it as USB-C for AI agents. Instead of writing bespoke tool integrations for each agent, the team builds MCP servers (HubSpot MCP, Notion MCP, internal-API MCP) that any Claude agent can consume. This cuts agent development time by 50 to 70% across a portfolio of use cases.
07How long does a Claude integration take to ship?+
A simple chatbot or summarization endpoint ships in 2 to 3 weeks. A full agent with tool use, RAG and observability ships in 5 to 7 weeks. Enterprise integrations with SSO, audit logs, multi-tenant guardrails and security review take 10 to 14 weeks. The team scopes the timeline on the audit call based on your use case and stack.
08Can you migrate us from OpenAI to Claude?+
Yes, frequent ask in 2025-2026. The team runs side-by-side benchmarks on your real tasks, identifies which prompts need rewriting (Claude prefers different prompt patterns than GPT), updates SDK calls, and ships a router that lets you A/B test or fall back. Most migrations complete in 3 to 5 weeks with no service interruption. Some teams keep both providers and route by task type. Crosslink: OpenAI agency.
09How do you keep Claude usage observable and under cost control?+
Three layers. (1) Langfuse or Helicone for prompt-level observability: every call logged with prompt, response, latency, cost. (2) Cost dashboards in Looker Studio with daily and per-user breakdowns. (3) Budget alerts in Slack when daily spend crosses a threshold. The team also implements per-tenant rate limiting if you run multi-tenant SaaS. Without these, a misconfigured agent can burn 5,000 USD overnight.
10What does the first free 60min audit cover?+
Review of your current AI stack (if any), your top 3 use cases for Claude, expected token volume, security and residency constraints. You leave with a written recommendation: which Claude model, which routing (Anthropic vs Bedrock vs Vertex), expected cost range, and a 4-week to 8-week implementation plan. No upsell pressure.
Hack'celeration Agency

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