Agentify

Build Production-Ready AI Agents for Enterprise Workflows.

Most enterprise agent projects stall between pilot and production. CurieTech closes that gap — building, deploying, and handing off production-ready agents that connect to your real systems, your real data, and your real workflows.

The Challenge

Enterprise Agents Fail for Predictable Reasons

These aren't model failures. They're infrastructure, integration, and process failures — and they show up the same way across every enterprise that tries to build agents without the right foundation.

Agents Work in Demos. They Break on Real Data.

Every agent demo runs on clean inputs and controlled scenarios. In production, data is messy, edge cases are constant, and the environment that made the demo look good is gone. The gap isn't the model — it's the architecture built around it.

Agents Can't Reach Your Actual Systems.

Enterprise agents need to connect to ERP, CRM, middleware, and legacy integration platforms — not just surface APIs. Most agent builders don't have that depth. They connect to what's easy and leave the business logic untouched.

Nobody Knows if the Agent Is Actually Right.

Without a structured evaluation framework, there's no way to know if the agent is producing correct outputs before or after go-live. Teams ship without confidence, discover failures in production, and lose trust in the entire initiative.

Our Approach

Built for Production from Day One

CurieTech doesn't build demos. Every engagement is structured around one outcome: a production-ready agent, deployed in your environment, with your team able to own and maintain it.

We connect to your integration layer at the code level — not just surface APIs — so agents reach the systems and business logic that actually drive your workflows.

Success Criteria Defined Before We Build

Every engagement starts by defining what success looks like — specific, measurable criteria the agent must meet before it touches production. We don't start building until we agree on what "done" means.

Connected to Your Real Systems

CurieTech's deep integration expertise — across 13+ middleware platforms — means agents connect to the systems that hold your real business logic, not just the ones with clean APIs. We reach what other teams can't.

Security and Governance Built In

Security reviews, compliance requirements, and IT approval are part of the engagement process — not discovered at go-live. Agents ship with full IT sign-off, not just developer confidence.

Results

What Production-Ready Looks Like

Every Agentify engagement ends with three deliverables — a deployed agent, full documentation, and a team that owns it. These are the outcomes we hold ourselves to.

Weeks
Scoping to Production

From first scoping session to a live agent in your production environment. Timeline varies based on agent complexity.

Zero
Surprises at Go-Live

Structured evaluation phase validates the agent before it touches production — you decide when to proceed.

Full
Team Ownership on Day One

Complete documentation, runbooks, and knowledge transfer — your team owns the agent from the moment it ships.

How It Works

A Structured Path from Scoping to Production

Every Agentify engagement follows three phases. Each has a clear deliverable and a defined role for your team — nothing gets handed off blindly and nothing surprises you at go-live.

Discover & Define

We map your workflows, systems, and success criteria before a line is built. Our agents inspect your integration layer at the code level to understand your environment from the inside out. This phase ends with a written scope: the agent's defined responsibilities, the systems it connects to, the success criteria it will be evaluated against, and a clear timeline.

Build & Integrate

We build the agent against your actual environment — real data, real edge cases, real integration constraints. CurieTech's deep middleware expertise means the agent connects to the systems that matter, not just the ones with clean APIs. Security and governance requirements are built in during this phase, not discovered at go-live.

Evaluate, Deploy & Hand Off

We run a structured evaluation against the success criteria from Phase 1 before anything goes live. Once the agent passes, we deploy to your production environment and complete a full knowledge transfer — documentation, runbooks, and working sessions with your engineering team. CurieTech remains available post-deployment for tuning as new edge cases emerge.

Deep Analysis

Why Most Agent Projects Fail — and Why Ours Don't

The failure modes are predictable. The fix is systematic. Here's how CurieTech addresses each one directly.

Typical Agent Projects

Built on clean synthetic data — breaks when it hits real enterprise data in production
Connects to surface APIs only — can't reach middleware or legacy integration logic
No evaluation framework — nobody knows if the agent is right until it fails in production
Security and compliance discovered at go-live — project stalls at the finish line
Handed off as code — your team inherits something they didn't build and can't maintain
Protocol Information

CurieTech Agentify

Built against your actual systems, real data, and real edge cases from day one
Deep integration expertise across 13+ platforms — connects to the systems that hold your real business logic
Structured evaluation at every phase — success criteria defined before a line is built
Enterprise-grade security and IT approval built into the engagement process from day one
Delivered with documentation, runbooks, and knowledge transfer — your team owns it from day one
Orchestration Workflows
Why CurieTech AI

The Credential Behind the Process

The Agentify process works because of what CurieTech brings to it — not just a methodology, but the technical depth to execute it in environments that stop other teams cold. Our agents are fine-tuned on 13+ enterprise middleware platforms — BizTalk, TIBCO, SAP PI/PO, IBM IIB, MuleSoft, and more — giving us code-level understanding of the systems that hold your real business logic.

We build on MCP (Model Context Protocol), exposing your middleware as agent-callable tools — the architecture that makes agents reliable in production, not just functional in a demo. Our founding team brings engineering experience from Meta, Uber, X, and AWS. We understand what production actually means inside a large organization.

Every engagement is outcome-based — not billed by the hour. We're scoped to a clear deliverable: a production-ready agent that meets the success criteria we defined together, with your team fully able to own and maintain it without CurieTech in the room.

CurieTech AI Advantage

Agents Built for Production, Not Just Demos

Deep integration expertise, MCP-native architecture, structured evaluation, and full knowledge transfer — the foundation that takes enterprise agents from pilot to production.

Get Started

Ready to Build an Agent That Works in Production?

Start with a scoping session. We'll map your workflows, define success criteria, and give you a clear engagement plan before you commit to anything.