Your team writes stories. Your AI agents write emails, replies, and documents. Both can look ready and still break the standards you care about. Pick the work you want checked.
Your next production defect is already in your backlog.
Vindex scores every story as it is written, inside Jira, Azure DevOps, Asana, or your AI client, and flags the vague, untestable, and oversized ones before anyone builds them.
Your agents never read your rules.
Vindex keeps one catalog of rules, checks each agent output against it, and names the rule that did not pass so the agent can fix it.
The question is who writes the work. People write stories. Agents write everything else.
| Question | Integrated Vindex | Agent Reflection |
|---|---|---|
| Who writes the work | People: product owners, analysts, coaches | AI agents |
| What gets checked | A user story | Any agent output: an email, a reply, a document, a story |
| Where it runs | Jira, Azure DevOps, Asana, your AI client, CSV, and the API | Your AI client or agent, over the Vindex MCP server |
| Who sets the standard | Vindex, with its story-quality method | You, with your own rules and public rules |
| What comes back | Story health as a whole percentage, with plain-language findings | Pass or fail for each rule, naming any rule that did not pass |
| How you pay | Per story, once | Per critique |
| Free to start | 5 stories with no signup, 100 with an account | 100 free critique credits with an account |
A story gets a health percentage and a plain finding. An agent output gets a pass or fail for each rule, and any rule that did not pass is named.
You
Score NW-108 with Vindex: “Warehouse scanning should be faster and better. The scanning process in the warehouse is slow and the team complains about it. Make scanning faster and improve the experience for the warehouse staff.”
Assistant
NW-108: 38% (At risk)
Add measurable acceptance criteria with baseline and target metrics (e.g., p95 scan-to-confirm time, scans/hour, error rate) and specify devices/network conditions for measurement.
Sample critique. Illustrative data written by Vindex. Not a customer result.
A company signs in once and finds Agent Rules beside its Integrated Vindex setup. The story-quality rule behind Integrated Vindex is also a public rule in the Agent Reflection catalog, and both products run on the same engine. What your team uses in Jira, your agents can use through the Vindex MCP server.
One sign-in covers both products. Both grants are one-time.
100
free user stories
Integrated Vindex
100
free critique credits
Agent Reflection
CSV files uploaded to the public evaluate page are deleted after 24 hours.
The Vindex MCP server signs in with OAuth 2.1, as a person in your company.
VindexAI reviews each Agent Reflection critique. No third-party model is involved.
BAA available. SOC 2 and compliance roadmap on request.
