Beta opens summer 2026

You should not have to learn AI
before AI can help you.

Tracegrain learns how the work actually happens: the tools, decisions, promises, and repeat steps behind a normal day. Then it turns that context into skills, scripts, and approved agents.

Get on the beta list →

No new workflow to memorize·Stays local by default·No external write without approval

01 · The problem

AI adoption is messier than the demos make it look.

Your best people are already doing the job. Sales is selling. Support is answering customers. Ops is keeping the business moving. They do not have spare time to test new tools, write perfect prompts, clean up bad outputs, and explain every workflow to a chatbot.

When AI gets it wrong, it does not save time. It creates another task. Tracegrain starts somewhere else: with the work already happening.

02 · The full-day context

The workday becomes usable context.

Today. Tracegrain turns raw capture into bounded events: meetings, app sessions, decisions, promises, Skill runs. The point is not to replay the day. The point is to give AI the context your team should not have to type in by hand.

09:08
Sales call with Sarah at Acme. Pricing tier migration discussed. Promise detected: send revised proposal by Friday.
meeting
10:21
Proposal edits across Notion, HubSpot, and Stripe. Same three-source pricing pull as last Tuesday.
work block
16:30
Daily recap generated: 4h 12m sales work, 3 open promises, 2 draft follow-ups, 1 pattern ready for review.
recap ready.

The timeline is the raw material. The working memory is what forms on top of it: people, promises, decisions, patterns, and proof.

Why the context matters

An agent without context is a very expensive blank page. Tracegrain gives it memory without making the team stop and brief it: what happened today, what usually happens, who matters, what was promised, and which work keeps coming back. The workday becomes the training.

03 · The system

Tracegrain sees the work, remembers the context, and helps with the repeat parts.

Most AI waits for someone to explain the job. Tracegrain builds the layer around the job first: Eyes, Brain, Hands, Body, Trust, and the Daily Surface. The context comes from the work, not from setup.

I

Eyes

Continuous capture, on the laptop.

Screen, audio, OCR, app focus, calendar. Always on, always local. Raw frames and transcripts never leave the machine.

II

Brain

A working memory that forms from the day.

The timeline becomes people, promises, decisions, topics, time, repeated patterns, and evidence. Not another model to train. Better context for the model you choose.

III

Hands

Safe ways to work inside your tools.

Custom CLIs and MCPs for the top systems your business already uses. Tracegrain learns which tools matter in the day, then gives agents approved paths to draft, prepare, and act.

IV

Body

Every Skill is a small package you can inspect.

Skills, prompts, permissions, scripts, and tests. The Body is what turns repeated work into a reusable agent instead of a one-off chat. Plain-text, inspectable, revocable.

V

Trust contract

No external write without your approval.

Every action is queued. Approve once, for the session, or always — explicit consent for each class of action. Pause is one click in the menu bar.

VI

Daily surface

The big picture, with receipts.

The page that tells you what is going on. Read the day in one paragraph, then zoom into the timeline, person, meeting, prompt, evidence, or Skill behind any claim.

04 · What arrives

By 6pm, the day has an answer.

Not another dashboard to babysit. A short readout of what happened, what changed, what needs follow-up, and which repeat work is ready for a Skill. Big picture first; receipts one click underneath.

Daily Recap → you
TODAY 18:00
Your day, reconstructed into useful context.

You spent 4h 12m across three sales calls, 1h 08m in proposal work, and 42m in Slack. Two promises are open: Sarah at Acme needs revised pricing by Friday; Mark needs the onboarding notes tomorrow.

One pattern is ready: the same pricing pull from HubSpot, Stripe, and Notion appeared for the third time in two weeks. Estimated time saved: 38m per run.

Generated from today’s timeline. · Runs locally. · Approve before anything writes.

Open timeline Draft follow-ups Review Skill
Skill daily-recap · Context timeline, people, promises, evidence · Runs 9am + 6pm

05 · Skills included

What Tracegrain builds from the workday.

LOCAL · APPROVED · AUDITABLE

These are not generic templates and they are not another tool for the team to learn. Each Skill gets the context it needs from the timeline: the meetings, people, promises, tools, and evidence behind the work.

Pattern noticed.
Daily Recap — what happened today, who you spoke to, what was decided, which promises are still open.
0.92
MON 08:14
Agent proposed.
Time Saved. Shows which approved Skills ran, what they replaced, and how much manual time came back this week.
MON 16:40
Approved.
ROI Report. Turns time saved, repeat frequency, and Skill activity into a weekly business readout. Useful for pricing, renewal, and deciding what to automate next.
TUE 07:29
Pattern noticed.
Follow-up Drafts — outbound emails from meetings, grounded in the actual conversation and the next step you promised.
0.88
WED 14:07
Agent proposed.
Promise Tracker. Finds commitments you made out loud and keeps them visible until there is evidence they were handled.
WED 15:22
Dismissed.
Timeline Search. Ask what happened around a person, project, meeting, or tool without scrubbing through recordings. Searches the semantic timeline, not raw footage first.
FRI 09:38
Agent proposed.
Skill Candidates. When the same work repeats, Tracegrain shows the evidence and lets you request the Skill that should exist.
FRI 17:12

“Your team should not have to learn AI before AI can help them. Tracegrain learns the work first, then builds the context agents need to be useful.”

— The work-first frame

06 · Over time

One day becomes a working memory.

The first day gives Tracegrain a timeline. The first month gives it patterns. By the time Skills start running, they are not guessing from a prompt — they are acting from context the team already created by working.

Day 1

1 timeline

Meetings, app sessions, promises, and decisions become bounded context instead of an eight-hour blur.

Week 4

6 patterns

Pricing pulls. CRM notes. Follow-up drafts. Weekly recaps. Pipeline rollups. Customer handoffs.

Quarter 1

12+ Skills

Daily recap, time saved, ROI report, promise tracking, follow-up drafts, and the repeat work that earned enough evidence to run.

07 · What we don’t do

Three things you won’t find here.

Not here No AI tool your team has to learn before it helps.
Not here No agent loose in your tools.
Not here No raw data off the laptop.

08 · When you’re ready

Each person gets their own working memory.

Tracegrain starts with you. When the daily brain proves itself on your own week, it extends to the people next to you — one invitation at a time, one private memory per person, formed from that person’s actual work.

No seat quotas. No rollout memo. No IT project. The team layer arrives the week you’d ask for it on your own.

  • Private by default. Each working memory belongs to one person, on their own laptop. Nothing crosses between them.
  • Results travel, not screens. What the team sees is hours back and patterns named — never each other’s work.
  • One invitation at a time. You decide who joins and when. No bulk provisioning.
  • Patterns compound across people. Each memory forms from its own person. The payoff shows up at the team level.

09 · The principle

You run your business. Tracegrain builds the brain from the work — then gives it approved hands.

Beta opens summer 2026. You’ll be among the first to try it.

Stays local by default·No external write without approval·See what it notices first.

Tracegrain.  —  Notices what you’ve stopped noticing.