The knowledge layer for physical work

Every thread of the work, aligned.

Physical Jobs scatter context across conversations, photos, manuals, measurements, people, and memory. CrossThread brings the work into one durable Job—so people and AI can see what is known, what is missing, what could happen next, and what actually happened.

Current founder build · invitation code required

Scattered contextOne durable Job
ACTIVE JOBEverything stays attached.Origin preserved · next move visible

01 / THE PROBLEM

Physical work loses knowledge at every handoff.

An incomplete report becomes another clarification call. A missing model number becomes another visit. A measurement stays in someone’s notebook. A decision disappears into a text thread. When context fragments, the next person starts over.

BEFORE

What brought us here?

What happened, photos, history, reported symptoms, and the information still missing.

DURING

What are we learning?

Questions, sources, measurements, evidence, decisions, and possibilities that remain open.

AFTER

What actually happened?

Work performed, release decisions, the observed outcome, and whether the result held.

CrossThread keeps those threads attached to the Job.

02 / THE WORKSPACE

One Job. Three synchronized views.

Conversation does the work. The record preserves orientation.

01

WORK

Choose where attention belongs.

Move across Jobs, requests, assignments, and follow-ups without losing the active problem.

02

CONVERSATION

Work through the physical situation.

Describe, question, correct, and decide continuously. Structure grows without replacing the person’s words.

03

PATHS

See what connects and what remains open.

Paths projects the record—what happened, what is unknown, and what could happen next—without becoming a second truth store.

Line up what you know, what you need, and what could happen next before you commit to changing the object.

03 / HOW IT WORKS

Carry the work forward without flattening it.

  1. 01

    Describe the Job

    Start in ordinary language and, when useful, add a photo. CrossThread separates the reported problem from what remains unclear.

  2. 02

    Get aligned

    The conversation organizes known facts, provisional AI ideas, open questions, risk, and possible next moves.

  3. 03

    Continue together

    The same Job carries context through requests, assignment, and handoff instead of beginning again in another system.

  4. 04

    Record what happened

    Work, decisions, release, and outcomes remain distinct records. Later check-ins preserve whether the result held.

04 / PROVENANCE

Every thread keeps its identity.

CrossThread does not turn people, AI, evidence, and records into one undifferentiated answer. It preserves where each piece came from and what it can—and cannot—establish.

Reported by a personProposed by AISupported by evidenceRecorded as workConfirmed as an outcome

05 / FIRST APPLICATION

Better information before the visit. Better record after it.

CrossThread is being shaped first for service teams that move a physical Job from reporter to coordinator to technician. Arrive better informed, avoid rediscovering the problem, preserve what the technician learns, and check whether the work held.

Founding service partner program in preparation
01Problem reported02Information organized03Job assigned04Technician continues05Work recorded06Outcome checked

06 / TRUST

Alignment is not authority.

CrossThread improves orientation without pretending that a model, map, or stored record has authority it does not have.

Organize the work. Preserve the basis. Keep consequential judgment human.
01

An AI proposal remains a proposal.

02

A reported attempt is not proof that it was performed correctly.

03

Paths can show a possibility; it cannot execute physical work.

04

Only an authorized person can accept a result or return an object to service.

CrossThread helps organize physical-work information and decisions. It does not certify repairs or replace qualified judgment.

07 / BUILD STATUS

Built in the open. Claimed carefully.

The live deployment is the founder’s working audit environment. Native packages, guided measurement, reviewed source retrieval, and the remote MCP service remain in development.

See what exists now

BY REACHABILITY LABS

The goal can remain after the route is gone.

Reachability Labs studies the gap between a goal and what a process can still reach. CrossThread applies that work to physical Jobs: make the unknowns visible, preserve viable paths, and align the next commitment with the evidence.

Visit Reachability Labs

CURRENT FOUNDER BUILD

Open the current CrossThread workspace.

The product is in founder-only development. The current workspace requires an invitation code.

Open CrossThread