FRAIM
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AI ENGINEERING

Meet AIDa

Agents that work. Evals that prove it. AIDa can design production AI agents, connect them to tools and data, and validate their behavior end to end.

What AIDa Can Build

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Job · create-ai-agent
Production AI Agent
Design, configure, and deploy an agent that is ready for real users.
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The Ask
A team can describe a use case and a target platform. AIDa can scope the agent design, instructions, tool/knowledge configuration, and deployment package.
What AIDa Can Build
An agent definition, platform-specific deployment package, tool permissions evidence, and a validation walkthrough against the intended use case.
Possible Outcome
A deployed agent with reviewable configuration, explicit tool allowlists, and a deployment receipt — not a chatbot prototype with undocumented permissions.
Supported Platforms
Microsoft Copilot Studio Google Vertex AI Agent Builder Amazon Bedrock AgentCore OpenAI Agents FRAIM / Local Configured Agent
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Job · author-ai-evals
AI Evaluation Suite
Author a runner-compatible eval suite with provenance, metrics, and a baseline run.
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The Ask
A team can supply a dataset, success criteria, and the agent or model under test. AIDa can structure evaluation cases covering task completion, tool use, hallucination, and safety.
What AIDa Can Build
A runner-compatible eval suite with dataset provenance, metric definitions, approval-evidenced thresholds, and an executed baseline result.
Possible Outcome
A committed eval suite runnable in CI, with a scored baseline, so future changes have a documented regression boundary rather than an untested guess.
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Job · enable-web-mcp
MCP Enablement for Existing Products
Expose an existing web product's approved capabilities through MCP.
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The Ask
A team can name the target web product and the capabilities to expose. AIDa can handle transport, authentication, least-privilege tool selection, and client connection instructions.
What AIDa Can Build
A functioning MCP server for the target product, with authentication wired, a tool manifest, and verified connection instructions for AI clients including Claude, Cursor, and GitHub Copilot.
Possible Outcome
AI agents that can call the product's real capabilities through a secured, documented tool surface — without exposing internal infrastructure or bypassing authentication.
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Job · evaluate-ai-agent
Agent Evaluation Run
Evaluate an existing agent for task completion, tool use, hallucination, and safety.
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The Ask
A team can supply a baseline agent and evaluation dataset. AIDa can run the evaluation using the platform's supported interface or the repository's existing eval harness.
What AIDa Can Build
A scored evaluation artifact linking each result to its evaluator, dataset version, run timestamp, and trace evidence location.
Possible Outcome
A reviewable evaluation report with per-case results and aggregated metrics, giving reviewers the evidence they need to approve or hold a deployment.