Build PoC AI Agents
Most agent ideas die on the drawing board or in slidecks after they’ve been presented.
Fortytwo help you design, build and validate production-ready proof-of-concept agents on Microsoft Foundry, establishing the agent architecture, evaluation criteria, and deployment runbook, so you can iterate safely toward production.
The Challenge
The build is no longer the hard part, as Foundry takes most of the friction out of building an agent.
What is left is doing it safely and getting it production-ready with grounding, evaluation, and a path to production.
Prompt injection and scope escape are real risks, even in a PoC, and an agent without identity and governance is a liability, not a prototype.
The Solution
A production-ready agent, evaluated and safe
Fortytwo helps you:
What We Deliver
Key Outcomes:
A working and evaluated AI agent aligned to a defined business use case, with the agent architecture documented and ready for security and governance review, with prompt injection and scope-escape risks identified and mitigated in the PoC. There is also a clear path to production, with governance and identity requirements defined.
AI Agent Design
An agent architecture and design blueprint, with framework selection and a context and memory strategy.
Working PoC Agent
A built and iterated agent with defined success criteria, grounded and callable from where your people work.
Agent Evaluation Framework
Structured evaluation for accuracy, groundedness, safety, and latency, with content filters and responsible AI controls.
Adversarial Testing
Testing against prompt injection and scope escape, with known failure modes and mitigations documented.
Handover Pack
Code, config, and a deployment runbook, with a path-to-production checklist and governance requirements.
How It Works
It starts with a current-state discovery, assessing your environment, identifying gaps, and defining next steps for governance, identity, and architecture. Then, we frame the use case and metrics, build the agent and test it against real and adversarial inputs, evaluating accuracy, groundedness, safety, and latency. Finally, we produce a handover pack and path-to-production checklist.
Related Services
FAQ
We need access to Azure AI Foundry, Copilot Studio, and Azure OpenAI, business and technical owners nominated for the agent, and participation in design and review sessions.
Yes. We select the framework to fit, and can use Semantic Kernel, AutoGen, or custom, and integrate tools via APIs, MCP, databases, and M365.
No. We build it production-aware, with evaluation, adversarial testing, and a deployment runbook, so the path to production is real.
Structured evaluation for accuracy, groundedness, safety, and latency, plus adversarial testing for prompt injection and scope escape, with documented mitigations.
Talk to Us
Get in touch if you want to discuss your challenges or questions.
Harri Jaakkonen
Principal Security Engineer
oi.owtytrofobfsctd-328c0d@nenokkaaj.irrah
Build the foundation and ship your first agent safely.
