Access by org line
Each leader sees only records about their own people. Anyone else on a record shows as "outside your line."
AI ROI agent for engineering leaders
Measure the Return on AI Across Your Engineering Teams
Tetrate PRISM is an AI ROI agent. Leaders ask questions in plain English and get answers that join AI spend with engineering output, for their own teams.
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Ask
Plain-English questions
Leaders ask. PRISM writes the query and runs it.
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Check
Answers you can check
Every number comes from a query on your own data.
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Govern
Access by org line
Each leader sees only their own people.
Inside PRISM
Ask a question, get the numbers behind it
A leader asks how AI spend compares with output on their team. PRISM answers with a table and a chart from the leader's own data.
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Ask in plain English
Type a question, or choose "What can I ask?" to see examples.
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Table and chart
Answers show the numbers for each person, with a chart when one helps.
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Question history
Past questions stay in the sidebar, so leaders can return to an answer.
The problem
Why AI ROI is hard to measure
AI spend and engineering output live in different systems, and no single system links them to the same person.
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Spend and output sit apart
AI cost sits in the AI gateway. Commits, tickets and project hours sit in other tools.
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No shared key
for peopleCode accounts often use personal emails. HR, project and ticket systems each use their own IDs.
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Reports lag
the questionEach new question waits for a new report. One CIO waited five months for a list of developers with no Git account.
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Access must follow the org chart
A leader should see their own teams, not the whole company.
How it works
From connected data to a checked answer
Four steps. Access rules apply before any answer.
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Connect context streams
An admin adds each dataset, such as GitHub pull requests or a Snowflake view, then tests and approves it.
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Link people to the org chart
PRISM matches people across systems by HR ID and email, and places each person under their leader.
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Ask in plain English
A leader asks a question. PRISM writes a query and runs it only on records about that leader's people.
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Check the answer
Answers show names, counts and trends. Each number comes from your database, so teams can compare it with existing reports.
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Mirror
History from APIs
PRISM copies history from systems such as GitHub and Jira, so it can answer questions over time.
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Query-through
Live data platforms
PRISM sends SQL to a data platform such as Snowflake and reads the result.
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Files
Spreadsheets
PRISM reads spreadsheets, such as a team roster in CSV or Excel, as one more context stream.
Example questions
Questions leaders ask PRISM
Real questions from engineering leaders, with the data each one uses.
| Question | Data used | What it shows |
|---|---|---|
| How many developers in my org have no pull requests this quarter? |
| Activity gaps |
| What did each team spend on AI last month, and how many pull requests did it merge? |
| Return on AI spend |
| Which pull requests were approved in under two minutes? |
| Code review risk |
| Which change caused this incident? |
| Incident cause |
| How many contractor architects report to each of my directors? |
| Workforce mix |
| Who are the top committers across GitHub and GitLab in my org? |
| Contribution |
Data integrations
Connect the systems your teams already use
Each dataset you connect is a context stream. One data source can have several.
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Code and builds
- GitHub
- GitLab
- GitHub Actions
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Work and service
- Jira
- ServiceNow
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Projects and time
- Jira
- Clarity PPM
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People and org
- Workday
- Any HR roster
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Data platforms
- Snowflake
- PostgreSQL
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Files
- Excel
- CSV
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AI spend
- Tetrate Agent Router Enterprise
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Sign-in
- Microsoft Entra ID
Context stream: One dataset that an admin connects to PRISM for questions, such as GitHub pull requests or one Snowflake view. Each context stream is one entry on the PRISM admin page, and that page sets the count. One data source can have several context streams.
Enterprise-grade
Built for enterprise security review
The controls a bank or a public company asks for before a new tool reaches leaders.
Single sign-on
Users sign in with Microsoft Entra ID. Admin and leader roles set what each person can do.
Audit log and usage page
Every question and answer is recorded. Admins see who uses PRISM and how often.
Admin glossary
Admins add the company's own terms and metric definitions, so answers use the words leaders use.
Self-hosted
PRISM runs in your own Kubernetes cluster. You install it with a Helm chart.
Standard Support
CVE fixes, bug fixes and version upgrades on a regular release schedule, with email and chat support on business days.
Customer story
A global fintech onboarded PRISM in 8 weeks
The CIO of a large technology group needed to see how AI changes engineering work, across thousands of engineers.
- 8 weeks Implementation and onboarding
- 8 Data sources connected
- 12 Context streams
- 46 Questions from leaders in the first 3 days
- Hidden gaps found: for the first time, the CIO saw which developers had no Git account or no commits.
- Code review risk: PRISM found review gaps, such as a bot that approved pull requests in under two minutes.
- Wider use: the customer plans to give access to peer leaders and operations teams, and to add more data.
For five months, I asked which of our developers had no Git account. PRISM answered that in seconds. Now PRISM will be a big part of our six-month tech transformation to build AI fluency across our teams.
FAQ
Frequently asked questions about PRISM
Tetrate PRISM is an AI ROI agent for engineering leaders. Leaders ask questions in plain English, and PRISM answers from the company's own data. It joins AI spend from Tetrate Agent Router Enterprise with engineering output from systems such as GitHub, Jira and ServiceNow, and shows the results by team and by person.
PRISM puts AI spend and engineering output side by side for the same people and teams. AI spend comes from Tetrate Agent Router Enterprise. Output comes from code, builds, tickets and project hours. Leaders can then compare spend with merged pull requests, closed tickets or project hours, team by team.
A context stream is one dataset that an admin connects to PRISM for questions, such as GitHub pull requests or one Snowflake view. Each context stream is one entry on the PRISM admin page, and that page sets the count. One data source can have several context streams.
PRISM connects to GitHub, GitLab, GitHub Actions, Jira, ServiceNow, Clarity PPM, Workday or any HR roster, Snowflake, PostgreSQL, spreadsheets, and Tetrate Agent Router Enterprise. An admin adds each dataset as a context stream, then tests and approves it.
No. With access by org line turned on, a leader sees only records about people in their own reporting line. Anyone else named on a record shows as "outside your line."
PRISM answers each question by running a query on your own data. The language model writes the query, and the numbers come from the database. Teams can compare any answer with their existing reports.
PRISM runs in your own Kubernetes cluster. You install it with a Helm chart, and users sign in with Microsoft Entra ID.
A global fintech implemented and onboarded PRISM in 8 weeks. In that time, its team connected 8 data sources and 12 context streams, set up access rules, and ran a two-week pilot with its leaders.
Start with the questions you ask today. Add data as you grow.
For engineering leaders
Tetrate PRISM
- Plain-English questions answered from your own data
- AI spend joined with engineering output
- Access by org line, single sign-on and an audit log
- Self-hosted in your Kubernetes cluster
- Tetrate Standard Support included
Need more help?
Bring three questions your leaders ask today. A Tetrate engineer will show how PRISM answers them on a demo deployment.