For hardware companies

Every build, every supplier, every lesson. In the agents your team already uses.

Design reviews, suppliers, tests and ERP. One memory.

Reads SAP and ERP systems, Jira, Linear, GitHub and 10 more

The problem

Every revision teaches something. Most of it is gone by the next one.

Cost

Paying for the same failure on every revision

Risk

Supplier terms one resignation away from gone

Time

Time lost reconciling design, orders and builds

By the numbers

The problem, in numbers

48%

of engineers search 1+ hour a day for parts

Source: Partsolutions

83%

of engineers recreate parts that already exist

Source: Partsolutions

1.8 to 3.6 hours

a day lost searching for information

Source: McKinsey; Coveo

~1.9M

US manufacturing jobs could go unfilled by 2033

Source: Deloitte

With Mithrandir

Before: Hours, weeks, months

With Mithrandir: Seconds

Up to 396 to 792 hours a year saved per person

Up to $12K to $24K

more revenue a year, per person

Source: McKinsey; Coveo; Damodaran · How it is estimated

Make your AI better

8.3×
lower AI cost
2.2×
faster answers
0
leaks in 30,000+ entries

How we measure

How much better it gets

In the agent each person already uses, within what they can access.

  1. Cost

    A failure that happened before

    Before

    The same failure is remembered after the rework is paid.

    After

    The earlier case, the fix and the test that proved it.

  2. Time

    Changing a part

    Before

    Nobody knows where the part came from, so the change waits.

    After

    The review, the alternatives and the supplier threads behind it.

  3. Cost

    Supplier history

    Before

    A buyer leaves and the supplier history goes too.

    After

    The full supplier history from email, calls and the ERP.

  4. Risk

    Engineering and operations on one page

    Before

    Manufacturing learns of design changes from the build.

    After

    Design changes, orders and builds, together.

  5. Time

    A new engineer on a program

    Before

    Months of decks and drives before real work starts.

    After

    How the program got here, revision by revision.

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 hardware

At 7:50 a test rig flags a connector failure on the new revision. The build review is at 10:00, and the VP of engineering asks Claude first.

“Have we seen this connector fail before, and what did we change?”

The VP of engineering · in Claude

The same failure two revisions ago, its root cause, the supplier who changed the plating, and the cost terms agreed with them, each with its source.

A new test engineer · in Copilot

The failure report, the root cause and the design change that fixed it. Supplier pricing stays with procurement and leadership.

The fix from two revisions ago goes into the build review. Nobody repeats the investigation, and the supplier terms stay with the people who own them.

95% of enterprise generative AI pilots show no measurable return. Source: MIT NANDA, The GenAI Divide, July 2025

Questions

Can it find a failure we already solved?
Yes. Ask in your agent and the past failure comes back with its root cause, the change that fixed it and the sources.
Are supplier terms kept private?
Each person sees only what they can access at work. Supplier pricing stays with the people your company has cleared for it.
Does it read ERP and engineering tools together?
Yes. ERP, tickets, drives, chat and email go into one memory, so design, orders and builds sit on one page.

See it on your own data.

One program: drives, tickets, email and ERP. Ask what your engineers ask.

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