The Anthropic agency.your models, under control.
Anthropic gives you Claude, an API key and some docs. What's missing is the enterprise rollout: picking the right model, securing your data, setting guardrails and keeping control of who uses what. That's the Anthropic agency's job. We frame the models, the security and the governance, US-based and remote.
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GeminiAn Anthropic agency frames your adoption, not just a POC.
Anyone can call the Claude API once. Picking the right Anthropic model, securing the data that flows through, and governing who uses what at company scale is a different job. Here are the four things we own.
- Anthropic models
The right Anthropic model for the right job
Anthropic doesn't ship one model, it ships a family: Opus for heavy reasoning, Sonnet for daily volume, Haiku when latency and cost come first. Pick at random and you're paying Opus for a job Haiku does for a fraction of the price, or the reverse and missing on quality. We map your use cases, route each task to the right model, and pin the versions so an Anthropic update doesn't break your production overnight.
See the model choice - API & platform
The Anthropic API wired in cleanly
An API key in a .env works for a demo. In a company you need workspaces split by team, quotas, rate limiting, token-cost tracking and alerts before the bill runs away. We set up the Anthropic SDK (Python or TypeScript), streaming, prompt caching to cut cost, and the monitoring that tells you who's spending what. You keep control of the Anthropic platform, not just a key lying around.
See the method - Security & data
Your data under control
The first question from a CISO: does Anthropic read or train on our data? By default, on the commercial API, Anthropic doesn't train its models on what you send. You still have to frame retention, redact personal data before the call, and block prompt injections trying to leak a context. We set up PII redaction, input and output guardrails, and a human check where the risk warrants it.
See the security - Governance & rollout
Govern Claude at company scale
Three teams each using Claude in their own corner, with no logs or rules, is an incident waiting to happen. We put usage policies, per-team permissions, audit logs and cost tracking in place, so Anthropic adoption stays steerable. Because we're an automation and AI agency first, we wire it all into n8n, Make and your SSO instead of letting each team reinvent its own glue.
See the governance
We deploy Anthropic like infrastructure, not a demo.
Most Anthropic projects stall in the same place: a demo that ran, then a block at the security review, because nobody framed the data, the models and the governance. So we treat it like infrastructure: the right model, secured data, governed usage, a team that knows how to run it.
- Audit · map the use cases, the sensitive data, and the security constraints
- Model · route each task to the right Anthropic model (Opus, Sonnet or Haiku) and pin the versions
- Secure · retention, PII redaction, guardrails against prompt injection
- Govern · usage policies, per-team permissions, audit logs and cost tracking
An automation agency, not a model reseller.
We don't sell an Anthropic partner tier. We come from automation and AI, so we see Claude for what it is: a strong engine that has to be wired in, secured and governed to be worth anything in the enterprise. That's exactly what's missing when a project ends at a demo that will never clear the security review.
- We come from automation and AI, not from reselling a model. Anthropic is a brick in your stack we wire in and govern, not the whole pitch.
- Model-agnostic: we pick Claude when it fits (reasoning, long context, safety) and say so plainly when GPT or an open model is the better call.
- We talk security and compliance before we code: retention, GDPR, DPA, prompt injection, instead of a POC that never clears the security review.
- No partner badge to wave. We're judged on whether Claude ships to production under control, not on a partnership tier.
Claude at the core, your security around it.
We build the parts that decide whether Anthropic ships or stays stuck at the review: the model choice, the data security, the governance. Then we connect it all to the tools your team already uses. Here's what a real rollout covers.
- Build
API integration & Anthropic workspaces
We wire the Anthropic API into your product and back-office with the SDK, streaming and structured outputs, and split workspaces by team to isolate keys, quotas and cost tracking.
- Build
Model choice & routing
We route each task to the right Anthropic model (Opus, Sonnet or Haiku) and pin the versions, so quality holds and a model update doesn't break your production without warning.
- Build
Data security & privacy
We frame retention, redact personal data before the call and document that the commercial Anthropic API doesn't train on your data, so the security review doesn't stall the project.
- Build
Guardrails & safety
We set up input and output guardrails against prompt injection and off-scope answers, with a human check where a model mistake is expensive.
- Build
Governance & audit logs
We put usage policies, per-team permissions, audit logs and cost alerts in place, so Claude usage stays traceable and steerable over time.
- Build
Compliance & enterprise rollout
We frame GDPR, Anthropic's DPA, SSO and data residency, and wire Claude into n8n and Make so the rollout follows your internal rules.
We scope your Anthropic usage, you leave with a plan.
Before quoting anything, we take 60 minutes to look at your use cases, your sensitive data and your security constraints. You leave with an honest read on which Anthropic model to use, what to secure first, and how to govern usage. Zero pitch, just an operator's take.
- Which Anthropic model for each case (Opus, Sonnet, Haiku)
- What to secure before you send data to the API
- How to frame GDPR, retention and Anthropic's DPA
- How to govern usage across several teams
How we deploy Anthropic in the enterprise.
Five steps, in order. We don't wire anything before the data and security are framed, we don't let wild usage take hold, and your team keeps control at the end. Each step has a deliverable and you sign off before we move on.
- Step 1 · Use & risk audit
Map the use cases and the sensitive data
We sit down with the people who own the topic (security, ops, product, legal) and list the Anthropic use cases in scope, the data that'll flow through, and the constraints (GDPR, confidentiality, latency, cost). You leave with a clear map of what can ship fast, what needs a guardrail, and what shouldn't touch a model at all.
- Step 2 · Model choice & routing
Route each task to the right Anthropic model
We test your real cases on the Claude family: Opus for heavy reasoning, Sonnet for daily work, Haiku when latency and cost matter. We set up the routing, pin the model versions, and cost out each use case so you know what every call costs before you scale.
- Step 3 · Secure data & prompts
Retention, PII redaction and guardrails
We frame retention on the Anthropic side, redact personal data before the call, and set up input and output guardrails against prompt injection and off-scope answers. Where a model mistake is expensive, we keep a human in the loop. The goal: clear the security review, not dodge it.
- Step 4 · Govern & roll out
Usage policies, permissions and audit logs
We split workspaces by team, set permissions, audit logs and cost alerts, and wire Claude into your stack (n8n, Make, SSO, API). Each team gets its own frame, you see who's spending what, and usage stays traceable. The rollout follows your internal rules instead of short-circuiting them.
- Step 5 · Train & hand over
Your team runs Anthropic without us on retainer
We train the people who'll manage day-to-day usage: how to read the logs, arbitrate between models, hold the cost and spot a risky prompt. The setup ships with a governance playbook. If you want to go deeper on building assistants, our Claude agency takes over. If you want us on call for what scales next, we talk about that separately.
We're judged on what ships and holds up.
No partner badge to display, so we lead with what matters: feedback from the teams we deployed Anthropic for, and whether usage stayed under control after we left. Our Trustpilot reviews come from those operators, not from a marketing deck.
- The rollout ships with a governance playbook
- Data secured, security review cleared before production
- Usage traced per team, cost under alert
- Trustpilot reviews come from the teams we deployed for
The questions we get asked on repeat.
What does an Anthropic agency actually do?
An Anthropic agency helps a company adopt Anthropic's models cleanly, instead of leaving you with an API key and some docs. We pick the right Claude model (Opus, Sonnet or Haiku) per case, wire the Anthropic API into your stack with isolated workspaces, secure the data (retention, PII redaction, guardrails against prompt injection), and set up governance: per-team permissions, audit logs, cost tracking. The point is Anthropic usage that clears the security review and stays steerable, not a POC that lives outside the rules.Does Anthropic train its models on our data?
No, not by default on the commercial API: Anthropic doesn't use the data you send through the API to train its models. It still has to be framed on the retention side and on what you send. We document this point for your security review, set up redaction of personal data before the call, and limit the context sent to the strict minimum. For sensitive usage, you can also go through Anthropic's DPA and frame data residency. It's usually the first question from a CISO, so we answer it in writing from the audit on.Opus, Sonnet or Haiku: which Anthropic model should we pick?
Depends on the job, and we test on your real cases before calling it. Opus for heavy reasoning and tasks where quality wins, Sonnet for daily volume with a solid quality-to-cost ratio, Haiku when latency and cost per call matter most. Most stacks blend all three with routing: Haiku rough-cuts, Sonnet processes, Opus settles the hard cases. We cost out each use case so the choice sits on numbers, not on a hunch.Is Claude GDPR-compliant for a European company?
It's something you frame, it isn't automatic. Anthropic offers a DPA (data processing agreement) and retention options. The rest depends on what you send and how you govern it: redact personal data before the call, limit retention, log access. We help you set up that frame (DPA, PII redaction, logs, data residency) so the project clears legal and security review. We won't sell you magical turnkey compliance: we put in place the concrete bricks that make it defensible.How do you secure the Anthropic API against prompt injection?
We treat prompt injection as a vulnerability, not a detail. Concretely: input guardrails that filter instructions hidden inside user data, output guardrails that block off-scope answers or ones trying to exfiltrate a context, and context sent kept to the strict minimum. For risky actions (reaching a system, sending an email), we keep a human in the loop or scope the tool's permissions. We test the whole thing by trying to break it before it goes to production.Claude or GPT for the enterprise: which one?
Depends on the case, and we're agnostic. Claude is solid on reasoning, long context, careful instruction-following and safety, which is why we often reach for it on document work, analysis and agents. But if GPT or an open model fits better on cost, latency or a specific capability, we'll say so. Plenty of companies run both and route by case. We don't have an Anthropic partner badge to defend, so the recommendation follows your use case, not our incentives.How do you govern Claude usage across several teams?
The real risk isn't a model that hallucinates, it's three teams each using Claude in their own corner with no rules. We split workspaces by team, set permissions and quotas, turn on audit logs and cost alerts, and define clear usage policies (which data is allowed to leave, which cases go through a review). You get a single view of who's spending what. That's what turns wild usage into an Anthropic adoption leadership can stand behind.How much does the Anthropic API cost and how do you control the bill?
The API usage you pay Anthropic directly, by token, and the price varies by model (Haiku the cheapest, Opus the priciest). What makes a bill drift is bad routing (sending everything to Opus) and no caching. We turn on prompt caching for the parts that repeat, route simple tasks to Haiku or Sonnet, and set cost alerts per workspace. On the agency side, we start with a free 60-minute audit to frame the scope before quoting anything.
Stop stacking POCs that never clear security. Deploy for real.
A 60-minute audit, your Anthropic usage scoped, a plan that holds on the models, the security and the governance. If your team can run it in-house after we ship, we'll hand you the playbook. If we're the right fit, we handle it.