PoC to Production: Our 90-Day Deployment Framework

When teams come to us with an AI use case, the first question is usually: “How long will this take?”

The honest answer is: it depends. But for a focused, well-scoped GTM agent — something like automated lead scoring, outbound personalization, or pipeline monitoring — 90 days is our target. Here’s how we use them.

Phase 1: Assess (Weeks 1–3)

Before writing a line of code, we need to understand what we’re actually building and whether the prerequisites are in place.

What we do:

• Use case validation. Is this the right problem to solve? Is there a simpler solution that doesn’t involve an AI agent? We’re direct about this.
• Data audit. What data does the agent need? Where does it live? How clean is it? This step alone often saves months of rework.
• Systems inventory. Which integrations are required? What are the API limitations? What permissions do we need?
• Success definition. What does a working agent look like, 90 days from now? We define this with the team before we start building.

What you get: A scoped implementation plan, a risk assessment, and a clear decision about whether to proceed.

Phase 2: Build (Weeks 4–10)

This is where we do the actual work — building the agent, wiring the integrations, and doing the unglamorous work of making it reliable.

What we do:

• Core agent development. Building the agent logic, designing the prompts, setting up the tools and data access it needs.
• Integration work. Connecting the agent to your CRM, SEP, and any other required systems. Building for reliability: retries, error handling, logging.
• Testing with real data. Running the agent against production data in a staging environment. Finding the edge cases and fixing them before they become incidents.
• Staging review. Working through the outputs with your team. Calibrating the agent’s behavior based on what they actually find useful.

What you get: A tested, integrated agent running in a staging environment.

Phase 3: Deploy & Optimize (Weeks 11–13)

Go-live isn’t the finish line. It’s the start of the data collection that makes the agent actually good.

What we do:

• Phased rollout. We don’t flip the switch for everyone on day one. We start with a small group of users, watch the outputs closely, and expand from there.
• Monitoring setup. Dashboards showing agent performance, error rates, and usage patterns. Alerts for when things go wrong.
• Team enablement. Training sessions for your team — reps, managers, and ops — on how to use the agent effectively and how to flag issues.
• Iteration. The first two weeks of production usage almost always surface improvements. We stay engaged through them.

What you get: A live agent with monitoring, an enabled team, and a clear handoff plan.

What makes this work

The 90-day timeline is achievable when a few things are true:

1. The use case is specific. Agents that do one thing well are easier to build, test, and operate than agents that do many things okay.
2. Data is accessible. We can work through data quality issues, but we need access to the real data early.
3. There’s a clear owner. One person on your team who’s accountable for the agent’s success after we hand it off.
4. Stakeholders are aligned. The teams who will use the agent are bought in before we start, not after.

None of these are hard requirements, but they’re correlated with success. The conversations we have in week one about these questions save weeks of rework later.

If you have a use case you’re trying to move from idea to production, let’s talk.