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Alphabyte·AI

Tools · Custom AI Agents

Custom AI Agents

Purpose-built task automation.

A custom AI agent executes a defined operational workflow end-to-end without someone manually running it. It connects to your data through MCP. It operates in an isolated cloud sandbox. It routes to a human at the decision points you define as requiring oversight. It runs in production, not in a demo environment that never ships.

Production systems with CI/CD pipelines, monitoring, and rollback capability. Built to the same engineering standards as any other production software in your organization.

Agents sit at the top of the stack. They depend on the AI reasoning layer for intelligence, MCP for data access, and your governance framework for guardrails. That is why we build agents after enablement and data connectivity are in place. An agent built before the team is using AI and data is connected produces a system nobody trusts and nobody uses.

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What we build

Agent sandbox and production runtime

Each agent developed and tested in an isolated cloud sandbox before production. A separate, stable production runtime provisioned for live agents with monitoring, alerting, and rollback from day one.

CI/CD pipelines for agentic workloads

Automated testing, deployment pipelines for agent code updates, rollback mechanisms for production incidents. Agentic development has specific requirements that generic CI/CD patterns do not address.

Agent Command Centre

Our observatory dashboard for the full agent estate. Real-time visibility into what every agent is doing, waiting on, completing, and flagging. Your team stays in control without inspecting logs.

Human-in-the-loop approval workflows

Every agent routes through approval workflows at the decision points your team has defined. The agent waits. The reviewer decides. Architectural requirement, not retrofitted governance.

Self-improvement feedback

Thumbs-up and thumbs-down correction flows that let your team flag incorrect outputs in real time. That feedback refines agent behaviour through hypercare and subsequent iteration.

Right for you if

  • You have enabled your team and validated your data, and are now ready to automate workflows end-to-end
  • You have clearly defined operational workflows that are high-volume and rule-governed
  • You want AI that runs in production, not a perpetual pilot

Not right for you if

  • Your team is not yet using AI consistently. Agents built before enablement produce systems nobody uses.
  • Your workflows are not yet well-defined enough to automate. Discovery or Citizen Dev comes first.

Frequently Asked Questions

Want to see what this looks like for your business?

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