THE PACEN AI INTEGRATION SPRINT ยท FIXED SCOPE PER PHASE
Pick the workflow that eats the most hours. We assess the code, restructure where needed, and build an AI agent or dashboard that works inside your existing systems. We test it on your real data and train your team to run it.
1
workflow, launch ready
Phased
scope and price agreed before each phase starts
100%
your code, your cloud
What you walk away with
An agent, assistant, or AI dashboard, deployable in your cloud and connected to the systems the workflow touches.
The code paths AI touches are restructured, covered by tests, and wired with alerts, so future changes carry less risk and your team knows the moment something looks off.
Real examples from your business, scored automatically each time the system changes.
Every build ships with an audit trail, sized to what your team needs to review, alongside accuracy, usage, and spend on one dashboard.
We train your team to run and monitor the new system and respond to alerts, with documentation and runbooks for key alerts.
A ranked shortlist of what we recommend automating next, with estimated effort and payback.
How a Sprint runs
Timeline is set during scoping, after we've seen your code, and written into each phase's quote.
STEP 1
Map the workflow, systems, and data access. Define the one number we'll use to measure success.
STEP 2
Trace in detail the code paths and data sources the AI will touch. Write the evaluation cases with your team.
STEP 3
Isolate and refactor what needs it, behind tests, so AI plugs in alongside your legacy logic.
STEP 4
The AI runs on real cases. You review its output side by side with your team's work.
STEP 5
Guardrails, approvals, permissions, and audit logging. A small group uses it daily while we tune.
STEP 6
Staged rollout plan and live monitoring in place. Your team trained to run the system and respond to alerts. Results reported against the step one metric.
INVESTMENT
Fixed scope per phase.
Clear deliverables and a price per phase before we start work. No open ended hourly billing. Every Sprint is scoped after a free call and a look at your codebase, then quoted by phase, each signed on its own. Half at kickoff, half at handoff. Model and cloud usage billed at cost to your own accounts.
Before anything changes, we put tests around the code AI will touch and roll out in stages with a fallback at every step. If we find deeper problems, you see them in writing before work starts.
We flag it in writing and scope it as its own phase, with its own price, before any extra work starts.
Nowhere new. We build inside your own cloud account and use enterprise model endpoints that don't train on your data.
Whichever scores best on your evaluation set at a cost you're happy with. We design so you can swap models later with minimal rework.
No. We need one decision maker, someone who knows the workflow, and access to the code. We handle the engineering and train your team to own it.
You own everything, and your team is trained to run it. We stay in your corner through the AI Partner Retainer for anything they can't solve.
You'll know at the prototype step, from your own evaluation data. If it isn't viable we stop, refocus on a better candidate, and tell you why.