Agentic AI · Featured pillar

Autonomous agents that execute — not just chat.

We design, build, and operate AI agents on the Microsoft Agent Framework, deployed via Foundry Agent Service, integrated through MCP — so your agents read, write, and act on the systems your business actually runs on.

Tell us your pain — proposal in 5 days See the Agent Pilot Sprint

StackMicrosoft FoundryMicrosoft Agent FrameworkMCPAzure AI SearchAzure OpenAIAutoGen

What we deliver

The full agentic stack.

From the first agent to a fleet of coordinated specialists — we engineer for production, not for a slide deck.

Custom AI agents

Single-purpose agents that execute well-defined tasks — built on the Microsoft Agent Framework with native Foundry deployment and tracing.

Multi-agent systems

Coordinator + specialist patterns, sequential and concurrent workflows, structured handoffs, and shared state via the Workflow API.

MCP tool integration

Connect agents to your enterprise stack via the Model Context Protocol — reuse the same MCP servers across IDEs, Copilots, and production agents.

Foundry Agent Service (GA)

GA March 2026. Managed runtime with private networking, MCP auth, Voice Live, and hosted agents — no Kubernetes needed. Supports Microsoft Agent Framework, LangGraph, and CrewAI.

Agentic process automation

Replace or augment business processes end-to-end — agents that decide, act, and escalate to humans when the rules say so.

Polyglot delivery

.NET and Python supported by the same framework. Reuse your existing engineering teams instead of forcing a rewrite.

Agent 365 + Entra Agent ID

Zero Trust for agents — every agent gets an identity in Microsoft Entra Agent ID, governed via Agent 365. Plus Microsoft's open-source Agent Governance Toolkit (OWASP agentic Top 10).

Evaluation & observability

Continuous evaluation pipelines, regression tests for non-deterministic systems, and tracing that lets you debug agent decisions.

Use cases

Where agents pay off fastest.

The patterns we deploy most often across mid-market and enterprise — every one already in production with at least one client.

Multi-agent customer service with intelligent escalation
Document processing — invoices, contracts, claims
Research and discovery agents over private + public knowledge
Sales SDRs and proposal-drafting agents
Compliance monitoring with audit-trail generation
Engineering productivity agents on top of GitHub Copilot

Process

How we deliver.

Four phases. Clear deliverables at each one. You can stop or hand off after any phase — no lock-in.

011 week
Discover
We map the workflow, identify agentic vs. non-agentic steps, and define success metrics. Output: a one-page agent brief plus a build/buy decision.
Output
Agent brief + decision matrix
021–2 weeks
Design
Solution architecture, agent topology (single vs. multi), tool inventory, evaluation criteria, and governance plan.
Output
Architecture + eval plan
033–8 weeks
Build
We engineer the agent on the Microsoft Agent Framework, integrate via MCP, ship to Foundry Agent Service, and run a closed pilot.
Output
Pilot agent in your environment
04ongoing
Scale
Production rollout, observability, FinOps, and continuous evaluation. We hand off, train your team, or operate it for you.
Output
Production agent + runbook

Why us

Microsoft AI specialists. Open-source contributors.

Pablo is a Microsoft MVP in AI and an upstream contributor to microsoft/agent-framework. When you hire Jextex you're not getting agency-tier consultants — you're getting practitioners who help shape the framework itself.

FAQ

Common questions.

Why the Microsoft Agent Framework?: It's the open-source SDK that GA'd on April 3, 2026 — the production convergence of Semantic Kernel and AutoGen under the Microsoft.Agents.AI namespace. Polyglot (.NET + Python), MCP-native, A2A-ready, and the runtime that Foundry Agent Service is built around. Pablo is an upstream contributor.
Can you work with our existing LLM provider?: Yes. The Agent Framework and Foundry support Azure OpenAI, foundation models from the Foundry Models catalog, and OpenAI-compatible providers. We help you choose based on cost, latency, and compliance.
How do you handle non-determinism?: We design with evaluations from day one — golden datasets, LLM-as-judge scoring, trace-based regression tests, and runtime guardrails. Our deliverable always includes an evaluation harness, not just the agent.
What about data security?: Agents run inside your Azure tenant. We use managed identities, scoped RBAC on Azure AI Search and Foundry, content safety filters, and PII redaction. We never train on your data.
Do you do single agents or only multi-agent?: Both — and we'll tell you which one your use case actually needs. Multi-agent is fashionable but not always the right answer; we default to the simplest architecture that works.

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