Agents Makers

SaaS

AI agents for SaaS.

Mid-market SaaS companies have the same operating-model problem at every stage: revenue is scaling faster than the headcount they can responsibly hire, and the gap is being filled by overworked Ops, Support, and CS teams running on second-best processes. AI roles are how this gap closes without breaking the unit economics.

The pattern that works: deploy hireable AI roles inside the teams that are already documented (Support, Customer Success, Operations, Finance), measure them against the metrics those teams already report, and let the Operating Partner handle scoping, governance, and the 90-day tuning cycle. No new system of record. No new dashboard. Just lower marginal cost on every workflow that scales with revenue.

The operating model in SaaS.

  • Plug into your existing stack

    Most mid-market SaaS runs on a known set of tools (Intercom or Zendesk, HubSpot or Salesforce, Stripe, NetSuite, Slack, Notion or Confluence). Every role in the catalog is built to read and write to those systems directly. No replatforming required.

  • Scoped to the team that owns the metric

    AI for SaaS works when the role is owned by a real team with a real KPI: Support owns FRT and CSAT, CS owns NRR and time-to-value, Finance owns DSO. The role plugs into that ownership instead of replacing it.

  • Measured on revenue-relevant metrics

    Support deflection that protects CSAT. Onboarding cycle time that pulls forward TTV. Collections automation that compresses DSO. Every role's KPI is something your board already reads on the monthly review.

  • Operating Partner handles the governance load

    Mid-market SaaS doesn't have a dedicated AI ops team and shouldn't need one. The Operating Partner owns scoping, deployment, weekly tuning, and the 90-day review. Your team's job is the metric, not the model.

How it rolls out

The playbook a real Operating Partner runs.

  1. Phase 1

    Pick the team with the most documented backlog

    Support and Operations usually win because they already have a queue, a runbook, and a metric. CS and Finance follow when SOPs are tighter.

  2. Phase 2

    Scope the first role, integrate to existing stack

    30-60 days from scoping kickoff to live deployment. Connectors land in your existing systems. No new tools introduced.

  3. Phase 3

    Run the role for 90 days under the guarantee

    Weekly tuning, monthly business review. KPI tracked on your existing dashboard. By day 60, leading indicators are visibly moving.

  4. Phase 4

    Expand to the next team or deepen the first role

    Most operators pick the second deployment based on what the first one taught them. Common second-wave: AR Specialist after Support, or SDR after Ops.

SaaS operators win by deploying AI roles where the metric, the runbook, and the team are already in place. Every role below is built to slot into that operating model.

Roles that fit this industry

26 roles

90-day operational guarantee. We agree on the outcome KPI before launch. If we haven't hit it by day 90, we keep working free until we do.

How it works →

Pick a role. Start deployment.

Every role in this view is hireable, governed, and anchored to the fully-loaded cost of the equivalent hire.