Anthropic consulting and implementation services
We specialize exclusively in Anthropic products: the Claude API, Claude Code, MCP, and agentic systems built on top of them. That narrow focus gives us depth — we know the platform inside out, not as one vendor among many in an integrator’s portfolio.
Three levels of engagement
Enable
1–2 weeksFor teams starting out with Claude Code who want to build competency fast
- Hands-on Claude Code workshops on your real tasks — no slides
- Team training in the fundamentals of agentic engineering
- AI-readiness audit: processes, data, infrastructure, risks
- Recommendations on tooling and environment setup
AI-readiness report with a prioritized adoption roadmap
Pilot
4–6 weeksFor teams ready to validate a hypothesis on a real production scenario
- Solution architecture design on the Claude API / Claude Code
- Production-grade implementation — not a throwaway prototype
- Integration with your systems and data
- Testing on real usage scenarios
- Handover of code and documentation to your team
A working pilot in your infrastructure plus architecture and design documentation
Scale
RetainerFor companies scaling a successful pilot across the whole organization
- Rolling the solution out to the whole team and adjacent processes
- Deploying the CCE (Swarm AI) platform
- Ongoing support: updates, quality monitoring, development
- Onboarding new staff and support for certification preparation
A working CCE platform in production plus a development plan
How we work
Discovery
We study your processes, data, and infrastructure over 1–2 weeks. Result: a report and an adoption roadmap.
Architecture & Security
We design the solution architecture and security model, including air-gapped setups where needed. Result: a design document.
Pilot
We build a production-grade pilot over 4–6 weeks. Result: a working product in your infrastructure.
Rollout + Training
We roll the solution out to your team and run training, optionally including preparation for the CCAR-F/CCAR-P certification.
Retainer
We support and develop the solution on an ongoing basis.
The hybrid architecture: how it works
Sensitive data never leaves the enterprise perimeter. Intelligence comes from both Anthropic and local models — the gateway layer handles routing, secret filtering and auditing.
Model requests pass through the gateway layer: secrets and personal data are filtered out before leaving the perimeter, sensitive workloads are routed to local models, the rest goes to the Claude API. Every call lands in the audit log.
What we do
Design the scheme around security requirements and budget
Deploy the cluster, the gateway, the agents and access policies
Train the team and support the solution after launch
Outcomes
- Data and secrets never leave the company perimeter
- Predictable cost: expensive models only where they are needed
- A single audit point for every AI call
- Infrastructure ready to grow: from a pilot to a cluster
AI infrastructure: on-premise and hybrid deployments
We design and deploy infrastructure for LLMs — from a single server to a full cluster. Your data stays inside your perimeter.
NVIDIA cluster configuration
Selecting and configuring GPU clusters (H200/B200): sizing for load, network topology, orchestration. Preparing for NVIDIA NCP-AII certification.
On-premise deployments
We deploy open models inside your perimeter: quantization (FP8/INT4), inference servers, per-token cost. We have experience sizing infrastructure for roughly 200,000 users.
Hybrid setups
Sensitive data stays on-premise, peak load bursts to the cloud. We set up routing between the Claude API and local models.
Isolated environments
Air-gapped environments with no internet access: agentic development and LLM work entirely within the customer's perimeter.
Corporate training
We train teams in Claude Code and prepare them for Anthropic certification exams directly within implementation projects — without pulling people off real work.
Training programs →