What brought us here?
What happened, photos, history, reported symptoms, and the information still missing.
The knowledge layer for physical work
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
01 / THE PROBLEM
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.
What happened, photos, history, reported symptoms, and the information still missing.
Questions, sources, measurements, evidence, decisions, and possibilities that remain open.
Work performed, release decisions, the observed outcome, and whether the result held.
CrossThread keeps those threads attached to the Job.
02 / THE WORKSPACE
Conversation does the work. The record preserves orientation.
WORK
Move across Jobs, requests, assignments, and follow-ups without losing the active problem.
CONVERSATION
Describe, question, correct, and decide continuously. Structure grows without replacing the person’s words.
PATHS
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
Start in ordinary language and, when useful, add a photo. CrossThread separates the reported problem from what remains unclear.
The conversation organizes known facts, provisional AI ideas, open questions, risk, and possible next moves.
The same Job carries context through requests, assignment, and handoff instead of beginning again in another system.
Work, decisions, release, and outcomes remain distinct records. Later check-ins preserve whether the result held.
04 / PROVENANCE
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.
05 / FIRST APPLICATION
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 preparation06 / TRUST
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.
An AI proposal remains a proposal.
A reported attempt is not proof that it was performed correctly.
Paths can show a possibility; it cannot execute physical work.
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.
BY REACHABILITY LABS
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 LabsCURRENT FOUNDER BUILD
The product is in founder-only development. The current workspace requires an invitation code.
Open CrossThread