AI AGENT TRACK FOR SAAS
AI Agent Track for SaaS: ship AI agent features without stalling your roadmap
The Modelcam AI Agent Track is a dedicated AI agent team that runs beside your core team. It designs, builds, evaluates and ships one AI agent feature into every release, on your stack, your models and your release cycle, connected to your customers' CRM, helpdesk and ERP.
- FOR
- SaaS and product companies
- ENGAGEMENT
- A dedicated AI agent team, sized per release
- WORKS ON
- Your stack, your models, your release cycle
- FIRST STEP
- One-Week AI Assessment of one feature
01 · THE PARALLEL TRACK™
How can a SaaS company add AI agents without stalling its roadmap?
Run AI agents on a parallel track. A dedicated Modelcam AI agent team builds beside your core team and merges one AI agent feature into each release, through your reviews and your QA. Your engineers stay on the roadmap you promised customers.
- 1Your core team. Keeps shipping the core roadmap. No engineers pulled off it.
- 2Modelcam AI agent team. Builds AI agent features in parallel, on your stack and your models.
- 3The merge. Each AI agent feature lands on your normal release.
- 4Your ground. Your codebase, your models, your brand. Customers see your product, not ours.
02 · THE AGENT LADDER™
What can an AI agent feature do inside a SaaS product?
It climbs four rungs. Each rung changes what the agent does, what your user does and how you can price it, moving your product from selling logins to selling outcomes.
- 1Assist. The agent suggests. Your user decides and acts.
- 2Act. The agent does one task. Your user approves it.
- 3Automate. The agent runs a whole workflow. Your user handles the exceptions.
- 4Accountable. The agent owns a result. You charge for the result.
03 · THE FOUR PROOFS™
How do you know an AI agent feature is ready to ship?
When it passes four proofs. Every feature the track team builds must be accurate, safe, connected and paid-for before it reaches your customers.
- 1Accurate. An evaluation suite built from your customers' real cases, re-run on every model change.
- 2Safe. Permissions mirror your user roles, with human approval where risk is high and every action logged.
- 3Connected. Tested inside your customers' CRM, helpdesk and ERP. Our edge: 23 years building IT systems for 250+ companies
- 4Paid-for. Moves one number you can charge for: adoption, resolution rate or time saved.
Who is the AI Agent Track for?
SaaS and product companies that have decided to add AI agents and need them shipped without slowing the core roadmap.
SaaS companies with a full roadmap
Your engineers are committed to customer promises. The track adds AI agent features without pulling anyone off them.
Product teams under pricing pressure
Agents are moving buyers from seats to outcomes. The track builds the rungs that let you price by result.
Platforms whose customers run complex stacks
Your agents must work inside customers' CRM, helpdesk and ERP. That integration work is where Modelcam has spent 23 years.
04 · TRACK ECONOMICS™
Should you hire an in-house AI agent team or run an AI Agent Track?
For speed and risk, run the track first. Hiring takes quarters before the first feature ships. The track ships its first AI agent feature around week 6, and you own everything it builds.
How does an AI Agent Track engagement work?
Prove one feature first, then keep the track running release after release.
- STEP 1 · WEEK 1
One-Week AI Assessment
Pick one agent feature. In a week we score its value, effort and data readiness and hand you a build plan.
How you pay: a fixed fee.
- STEP 2 · FROM WEEK 2
AI Agent Track
A track lead in your time zone, two or three agent engineers and an evaluation and integration engineer. First feature ships around week 6.
How you pay: monthly, sized each release cycle.
- OPTIONAL
Upside share
Tie part of the fee to the AI agent feature's adoption or revenue, so we share the outcome with you.
How you pay: a share agreed up front.
Questions about the AI Agent Track
Updated 21 October 2026
What is the Modelcam AI Agent Track?
A dedicated AI agent team that works beside your core engineering team. It designs, builds, evaluates and ships one AI agent feature into each release of your product, on your stack, your models and your release cycle.
How is it different from hiring AI engineers or staff augmentation?
You get a working team with a delivery method, not individual contractors. The track arrives with the Four Proofs™ playbook, ships on your release cycle and hands over everything it builds.
Which models and tech stack do you work with?
Yours. The track builds inside your codebase and uses the models you already run or choose. We do not lock you into our own platform.
What is the Agent Ladder™?
Modelcam's four-rung model for AI agent features: Assist, Act, Automate and Accountable. Each rung changes what the agent does, what the user does and how the feature can be priced, from per seat to per outcome.
What are the Four Proofs™?
The checks every AI agent feature passes before it ships: Accurate (an evaluation suite built from real customer cases), Safe (permissions, approvals and an audit trail), Connected (tested inside customers' CRM, helpdesk and ERP) and Paid-for (it moves a number you can charge for).
How soon does the first AI agent feature ship?
Typically in week 6: a one-week assessment, four weeks to build and pass the four proofs, then release on your normal cycle. After that, a new feature or a new rung each cycle.
Who owns the code, prompts and evaluations?
You do. Source code, prompts, evaluation suites, guardrails, connectors and dashboards belong to you after every release.
Can the agents work with our customers' CRM, helpdesk and ERP?
Yes. Connection is one of the four proofs. Modelcam has spent 23 years building IT systems for more than 250 companies, so integration with real enterprise systems is where we start.
How is the AI Agent Track priced?
A fixed-fee One-Week AI Assessment, then a monthly track sized to each release cycle. You can tie part of the fee to the feature's adoption or revenue.
Pick one agent feature. We will score it in a week.
A One-Week AI Assessment of one feature gives you value, effort, data readiness and a build plan.