01 Agentic AI Solutions
Autonomous agents that do real work.
Custom single- and multi-agent systems that plan, use tools and collaborate across support, operations, finance and engineering. Built for production from day one.
AGENTIC AI Architect · Build · Optimize
Engineering the agentic enterprise.
Cloudworkbench designs, builds and tunes autonomous AI systems: multi-agent platforms, agentic Git workflows and production-grade AI services that make it past the pilot.
Model-agnostic · Cloud-native · Built on your stack
Anthropic ClaudeOpenAIGoogle GeminiModel Context ProtocolAWS BedrockAzure AI FoundryVertex AILangGraphKubernetesGitHubGitLabOpenTelemetryPostgres + pgvectorTemporal
Anthropic ClaudeOpenAIGoogle GeminiModel Context ProtocolAWS BedrockAzure AI FoundryVertex AILangGraphKubernetesGitHubGitLabOpenTelemetryPostgres + pgvectorTemporal
Services
Everything you need to put agents to work.
From the first architecture review to agents running in production. One senior team covers strategy, engineering and ongoing optimization.
02 Architecting Agentic Systems
Blueprints that scale past the demo.
Reference architectures for agent topology, tool layers, memory, state and security, designed around your cloud and your constraints.
03 Optimizing Agentic Systems
Faster, cheaper, more reliable.
End-to-end profiling, then tuning of prompts, routing, caching and tool calls against eval suites. Quality goes up while cost and latency come down.
04 Agentic Git
Version control for an autonomous workforce.
Git-native workflows where agents branch, commit, review and open pull requests, with semantic diffs, policy gates and full provenance on every change.
05 AI Services
From strategy to shipped, end to end.
The foundations every agent stands on: LLM integration, retrieval and knowledge systems, fine-tuning, evaluation and AI readiness for your cloud.
Agentic Git
Git, re-engineered for autonomous teams.
When agents write code, you need more than a repository. You need isolation, review and an audit trail built for machines working beside people.
Branch-per-agent isolation
Every agent works in its own branch and sandbox. Nothing reaches main without review.
Semantic diffs & risk scoring
Reviewers, human or agent, see intent and blast radius, not just changed lines.
Human-in-the-loop gates
Policy-driven approvals at the moments that matter: migrations, auth, money and prod.
End-to-end provenance
Signed commits trace every change to the prompt, model, tool calls and evals behind it.
Process
A clear path from idea to production.
Short, outcome-driven phases. Every phase ends with something you can run, measure or put in front of a stakeholder.
01
Discover
Map workflows, data and systems, then find where autonomy pays off and where it shouldn't be used.
Output · Opportunity map
02
Architect
Design agent topology, tool and MCP layers, memory, guardrails and evals, all fitted to your cloud.
Output · Reference architecture
03
Build
Ship agents into your environment with agentic Git, CI evals, tracing and policy gates from the first commit.
Output · Production pilot
04
Optimize
Continuous evals, model routing, caching and prompt and tool refinement keep quality up and costs down.
Output · Measured ROI
Why Cloudworkbench
Built for production, not demos.
Most agent projects stall between prototype and production. We build the engineering discipline that gets them across.
0%
Average reduction in inference spend after an optimization sprint
0×
Faster pull-request cycle time with agentic Git workflows
0 wks
Typical path from discovery to a production pilot
0%
Of agent actions traced, evaluated and attributable
Evals before vibes
Every agent ships with a regression suite covering task success, tool accuracy, safety and cost, tracked on every change.
Observability built in
Traces across every plan, tool call and hand-off. OpenTelemetry-native and delivered into your existing stack.
Guardrails & governance
Least-privilege tool access, policy engines, PII controls and audit trails your security team can approve.
Model-agnostic, cloud-native
Claude, GPT, Gemini or open-weight models, routed per task and deployed in AWS, Azure or GCP inside your VPC.
Let's build
Put your first agent workforce into production.
Tell us about the workflow you want to automate. We'll reply with an initial architecture view and a practical path to production.