1. Instrument
An agent reads your codebase and adds explicit step() calls at real product moments, such as account creation or first value.
← OnRamp Analytics
Agentic analytics for product teams
Let your coding agent set up and investigate product analytics
OnRamp gives coding agents a controlled way to instrument meaningful onboarding milestones, define conversion funnels, and inspect the evidence behind drop-off. Your team keeps control of authorization and destructive changes.
2. Configure
With an organization-approved CLI session, it can create a project, turn those steps into a funnel, and add useful segments.
3. Investigate
It can read conversion, retention, breakdown, and exit-path data to make a grounded next-step recommendation.
What is agentic analytics?
Agentic analytics is analytics work performed by an AI agent with clear boundaries. Instead of only answering a question about a dashboard, the agent can use approved tools to complete parts of the workflow: understand the product, add the events needed to measure it, configure the report, and inspect the result.
For product analytics, the useful boundary is not broad access to every data system. It is a narrow, auditable set of actions around the customer journey. OnRamp's CLI is built for that workflow: it can create projects, manage funnels and segments, manage ingestion keys, and read analytics. It has no delete command; destructive changes remain in the dashboard behind a typed confirmation.
Agentic analytics vs. traditional BI tools
Traditional BI tools are designed around an analyst creating reports over broad company data. They are useful for that job. Product teams often have a tighter question: where do people abandon onboarding, what changed by app version or acquisition source, and what should we fix next?
OnRamp focuses an agent on those product questions. The agent works from named milestones and funnels rather than guessing from raw logs, and the results stay tied to real users, versions, platforms, referrers, retention, and tracked navigation paths. That makes the recommendation inspectable instead of a generic AI summary.
A practical agentic analytics workflow
- Ask the agent to find three to five meaningful onboarding moments in your codebase.
- Have it add OnRamp SDK calls at those moments and propose the funnel before it changes code.
- Authorize the CLI in your browser, then let the agent create or update the funnel for the new step names.
- After traffic arrives, have it inspect conversion and breakdowns, then recommend one measurable improvement.
The product onboarding analytics workflow remains useful even when an agent performs the setup: event names need to represent real user progress, and a human should decide which product change to ship.
Use a coding agent without giving up control
Browser login grants the CLI access to your organization rather than exposing a password to the agent. You can also use scoped app or project-creation tokens for automation. The CLI returns JSON by default, which lets an agent use the result safely in the next command. Access can be revoked from OnRamp settings at any time.
Try agentic analytics on your onboarding
Create an OnRamp project, copy the setup prompt into your coding agent, and turn your first real milestones into a funnel.