For software companies
Your whole company, in every agent your team already uses.
Code, tickets, calls and chat. One memory.
Reads GitHub, Jira, Linear, Slack and 8 more
The problem
Your agents write code fast. They know nothing about your company.
Cost
Paying agents to relearn the company every session
Time
Engineering time spent relearning old systems
Revenue
Deals and renewals waiting on an engineer
By the numbers
The problem, in numbers
- 1.8 to 3.6 hours
a day lost searching for information
Source: McKinsey; Coveo
- ~25%
of the workweek spent searching
Source: Atlassian
- 44%
say fragmented data blocks automation
Source: SAPinsider
- 50%
of developers lose 10+ hours a week
Source: Atlassian
With Mithrandir
Before: Hours, weeks, months
With Mithrandir: Seconds
About 10 seconds
to find the story across thousands of documents.
Up to 396 to 792 hours a year saved per person
Up to $7K to $14K
more revenue a year, per person
Source: McKinsey; Coveo; Damodaran · How it is estimated
How much better it gets
In the agent each person already uses, within what they can access.
Time
How a part of the product works
Before
The context is in a thread, a ticket and an engineer who left.
After
The history, the rejected options and the thread it came from.
Cost
An incident comes back
Before
The postmortem turns up after the fix.
After
The earlier incident and its fix, while it still matters.
Revenue
Customer commitments and the work
Before
Engineering hears about a promise when the customer escalates.
After
The commitment, the account and the work, together.
Time
Support with engineering context
Before
A ticket, a meeting, and an answer three days later.
After
Support asks their own agent. No meeting.
Cost
Agents that know your history
Before
The same background pasted into every session.
After
Claude, Cursor, Copilot or Codex start with what the company knows.
Safe on every row.
Only what you can already access
Your hierarchy, the way it should be
Walls that hold, for every agent
0 leaks, 100% sourced, 30,000+ entries. How we measure · Security
A scenario
One Monday morning in software
At 8:15 an enterprise customer reports that exports are failing again. The account renews next month. Before standup, the CTO asks Cursor what the company already knows.
“Has this export failure happened before, and what did we promise this customer?”
The CTO · in Cursor
The incident from March, the fix and its pull request, the call where sales promised a fix date, and the renewal terms, each with its source.
A new support engineer · in Claude
The incident, the fix and the support tickets on the account. The renewal terms and the pricing thread stay with sales and leadership.
The fix ships by noon, the account lead calls back with the right promise, and nobody spends the morning rebuilding history from old threads.
90% of professional developers use AI coding agents every week. Source: JetBrains Research, August 2026
Questions
- How is this different from giving agents repo access?
- Repo access shows the code. Mithrandir adds the history around it: the tickets, the calls, the incidents and the decision behind each change, sourced, in the same agent.
- Does it work with Cursor, Claude and Copilot?
- Yes. Mithrandir works with 20 agents over MCP, including Cursor, Claude, Copilot and ChatGPT.
- Can sales and support ask too?
- Yes. The whole company shares one memory. A support lead and an account executive get answers within their own access, without waiting on an engineer.
See it on your own data.
Connect repos, tickets and chat. Compare the answers to what you get today.
Remember.
Every company needs agents that know it. We are here for that.
Remember more. Spend less.Bring one workflow. See it on your own data in 30 minutes.
Last updated 21 October 2026 · Mert Uzun, co-founder