Use Case

Enterprise agent platforms & automation builders

Operate thousands of customer-specific agents with confidence, prevent regressions and uncover what to automate next.

Enterprise platforms don't ship one assistant. They ship endless variations across customers, roles, and workflows.

Chatching gives you the visibility to prevent breakage and the insights to grow usage and revenue.

Best fit if your agent library is growing faster than your ability to verify and improve it.

This Use Case

This is for platforms that let enterprises build and run many agents/automations across teams and workflows, where each customer configuration creates new behavior to maintain.

The Challenge

The agent explosion problem

As you scale, you don't just add features, you add behaviors.
Across customers and use cases, the number of agents and variations grows fast, and the system becomes:

Brittle:small changes cause unexpected breakage
Inconsistent:the same intent gets different behavior across customers
Hard to verify:no clear "safe to ship" standard across scenarios
Hard to debug:when something fails, it's unclear why
Hard to measure:you can't see which agents drive outcomes and adoption
Hard to prioritize:it's unclear what capability to build next to grow usage

That's how platforms end up stuck between shipping slower or breaking trust.

What We Provide

What Chatching helps you do

Regression: prevent breakage and ship safely

Know what's broken, why, and whether a release is safe.

  • Create high-quality eval sets that reflect real customer scenarios
  • Run regression testing before production releases
  • Detect failure modes: hallucinations, wrong action, partial success
  • Set quality thresholds tied to business risk ("safe to ship" gates)
  • Produce actionable "what broke and how to fix it" reports for teams

We can set this up with tools like Langfuse or Braintrust so your team can own it.

Progression: grow usage and revenue based on real demand

Know what users are trying to do — and what to automate next.

  • Identify repeat requests and unmet needs across customers
  • Cluster "what users are trying to do" into buildable agentic capabilities
  • Prioritize what to build next based on adoption potential and impact
  • Provide a roadmap of "next automations" that drive platform usage growth
  • Track whether new capabilities actually increase repeat usage and outcomes

Want regression + progression visibility for your platform?

Deliverables

What you get

  • A regression-ready eval and testing plan (plus recommended thresholds)
  • A repeatable pre-release regression process
  • A failure mode view: what breaks, how often, and why it matters
  • A demand map: what users are trying to do across customers
  • A prioritized "what to automate next" roadmap tied to adoption and revenue
Getting Started

Where to start

Most platforms start with a focused Technical Audit to identify:

  • Where regressions are slipping into production
  • What's missing to verify quality at scale
  • What demand signals should drive the next capabilities you build

Scale your agent platform without losing trust

If your agents are multiplying faster than your ability to verify and improve them, Chatching helps you prevent regressions and find the next automations users actually want.

We'll reply with a short intake form and suggested next steps.