Workspace

Where your team and agents
do the work, side by side

Fig. 1Context Workspace
Q2 attribution Open in Drive Files Activity Share
You08:30

Compile the Q2-to-date attribution package. IC review is Friday, and they want the writeup and the underlying numbers in one place.

Context08:30

Pulling the attribution rows from Snowflake and the factor scorecards. Going to ship a .docx + .xlsx pair.

Q2 attribution
Done in 2 min 04 s
  1. Pull daily attribution Q2 to date, 104 rows
  2. Compute factor & sector decompositions, Snowflake
  3. Compose writeup, 3 sections
  4. Render spreadsheet, attribution sheet
  5. Wrote factor-decay-2026-05-26.docx, 84 KB
  6. Wrote p&l-attribution-may-w22.xlsx, 412 KB
Wrote factor-decay-2026-05-26.docx, 84 KB
factor-decay-2026-05-26.docxworkspaces/b/q2-attributionDoc · 84 KB
Wrote p&l-attribution-may-w22.xlsx, 412 KB
p&l-attribution-may-w22.xlsxworkspaces/b/q2-attributionSheet · 412 KB
Context08:33

Package ready. Writeup in the .docx; underlying numbers in the .xlsx with one tab per factor.

factor-decay-2026-05-26.docx84 KB · for IC reviewp&l-attribution-may-w22.xlsx412 KB · 8 factor tabs
You08:40

The momentum decay row needs context. Footnote the schema-pin patch underneath.

Context08:40

Footnote added. Cites incident-2026-05-26 + PR #4181 + the vendor-schema-drift-watch rule. Both files updated in place.

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Posts the .docx + .xlsx pair to the channel and pings d. ortiz.
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factor-decay-2026-05-26.docx
Document

Q2 attribution

Sep 10, 2026 · Q2 attribution · Context

Package ready. Writeup in the .docx; underlying numbers in the .xlsx with one tab per factor.

Footnote added. Cites incident-2026-05-26 + PR #4181 + the vendor-schema-drift-watch rule. Both files updated in place.

What was checked

Pull daily attribution (Q2 to date): 104 rows

Compute factor & sector decompositions: Snowflake

Compose writeup: 3 sections

Workspace is where people and agents complete tasks together, on the same files in the same environment. Skills define the work in plain English, and every action becomes a trace your team owns.

Plain-English skills

One surface for people and agents

A trace on every run

Side by side

People stay in control

A person and an agent work the same task in the same place. The agent does the legwork; the human approves the calls that matter.

  • Live cursors and shared files, so a handoff is a glance, not a re-brief.
  • Sensitive actions wait for a person; routine ones run on their own.
  • Every step is on the record, so review is reading, not reconstructing.
WorkspaceDrafting weekly customer health review

Reviewing 12 strategic accounts to flag ARR at risk this quarter.

Pulled usage and tickets
Flagged 2 at-risk accounts
Drafted summary memo

Built for work, not just chat

The surface carries the whole job, from the skill that defines it to the trace it leaves behind.

Plain-English skills

Anyone can describe a workflow in plain English. It becomes a durable team artifact others can run, inspect, and improve.

A computer per agent

Each agent gets its own sandboxed environment to run commands, navigate files, and execute code, not just a chat box.

The same files

People and agents work the documents, sheets, and decks together, with a clean handoff in either direction.

Any model or agent

Claude, GPT, Gemini, Kimi, or open weights. Bring your own agent framework, or use ours.

A trace on every run

Every action is captured as a complete, replayable trace, so the work is auditable by the team accountable for it.

Applets for the task

Agents generate a fit-for-purpose interface for a workflow, so the team works in the view the task needs.

Model-agnostic

Use any model, switch anytime

You are not locked into one AI model. Pick the best one for each task, and routine work runs on the cheapest model that still does it well.

  • Claude, GPT, Gemini, Kimi, and open weights, side by side.
  • Per-task model choice, with the run recording which model handled it.
  • Swap models without rewriting the skill the team relies on.
acme-q4-diligence
Acme · Q4 review
Draft the diligence memo for Acme — focus on Q4 risks and growth signals.
Pulling Acme's Q4 financials, support tickets, and customer calls.
acme-q4-financials.csv+247 rows
Drafting risk signals and growth opportunities from the calls.
diligence-memo.docx+89 lines
Done — 3 risk signals, 2 growth opportunities flagged.
Ask anything (⌘L)
Research
Models
Claude 4.5 Sonnet
GPT-5
Gemini 2.5 Pro
Kimi K2
Llama 4 (custom)
Fig. 2Edit a skill in place
Q3 portfolio review deck Open in Drive Files Activity Share
You09:20

Build the Q3 review deck from the updates doc and the valuation bridge. Same structure as Q2, the three flagged companies up front.

Context09:20

Reading the Q3 updates and the bridge workbook, then drafting from the Q2 template.

Q3 portfolio review deck
Done in 3 min 48 s
  1. Read q3-portfolio-updates.docx, 14 companies
  2. Read q3-valuation-bridge.xlsx, 3 scenarios
  3. Draft slides from the Q2 template, 18 slides
  4. Place the flagged companies first, Northwind, Fenwick, Alder
  5. Render q3-portfolio-review.pptx, 4.1 MB
  6. Wrote q3-portfolio-review.pptx, 4.1 MB
Wrote q3-portfolio-review.pptx, 4.1 MB
q3-portfolio-review.pptxworkspaces/b/q3-portfolio-review-deckDeck · 4.1 MB
Context09:24

Deck is ready: 18 slides, the three variance companies on slides 3 to 5 with the covenant tests beside each, the full portfolio table in the appendix.

q3-portfolio-review.pptx4.1 MB · 18 slides
You09:31

Add the covenant headroom chart from the workbook to the Fenwick slide.

Context09:31

Added. Slide 5 now carries the interest-cover chart with the 2.0x test line; the appendix table is unchanged.

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Posts q3-portfolio-review.pptx to the channel and notifies the four members.
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q3-portfolio-review.pptx
Deck

Q3 portfolio review deck

Sep 10, 2026 · Q3 portfolio review deck · Context

Deck is ready: 18 slides, the three variance companies on slides 3 to 5 with the covenant tests beside each, the full portfolio table in the appendix.

Added. Slide 5 now carries the interest-cover chart with the 2.0x test line; the appendix table is unchanged.

What was checked

Read q3-portfolio-updates.docx: 14 companies

Read q3-valuation-bridge.xlsx: 3 scenarios

Draft slides from the Q2 template: 18 slides

Built for production work.

The Context on-prem appliance with its inference accelerator visible inside.

Run anywhere.

Hosted. Your VPC. Air-gapped. The on-prem Context appliance.

Use any model or agent.

Claude, GPT, Gemini, Kimi, or open weights. Bring your own agent framework, or use ours.

acme-q4-diligence
Acme · Q4 review
Draft the diligence memo for Acme — focus on Q4 risks and growth signals.
Pulling Acme's Q4 financials, support tickets, and customer calls.
acme-q4-financials.csv+247 rows
Drafting risk signals and growth opportunities from the calls.
diligence-memo.docx+89 lines
Done — 3 risk signals, 2 growth opportunities flagged.
Ask anything (⌘L)
Research
Models
Claude 4.5 Sonnet
GPT-5
Gemini 2.5 Pro
Kimi K2
Llama 4 (custom)

Enterprise-grade authorization.

Identity through your IdP. Customer-managed keys. Audit on every action. Permissions inherited at every connector call.

Audit loglive
S
sarah.chenSnowflake
select · 47 tables in finance.sales
09:42
M
marcus.leeGoogle Drive
edit · Q4-memo.docx
09:38
P
priya.shahJira
comment · ENG-4421
09:36
A
ana.martinezSlack
post · #risk-review
09:34
acme-q4-diligence
diligence-memo.docx
Acme Q4 Diligence
Summary
Acme closed Q4 above plan on revenue, with margin compression from a one-time integration spend. Pipeline coverage for Q1 is healthy at 3.1x.
Risk signals
•Top-5 customer concentration up to 41%.
•Churn in mid-market segment ticked to 4.8%.
•DSO extended by 6 days versus Q3.
acme-q4-financials.xlsx
A
B
C
1
Metric
Q3
Q4
2
Revenue
$1.04M
$1.23M
3
OpEx
$0.71M
$0.88M
4
Margin
31.7%
28.5%
5
Pipeline
$3.1M
$3.9M
6
Churn
3.2%
4.8%
7
NPS
47
52

A complete working environment.

Documents, spreadsheets, decks, kanbans, and file viewers built in. Your team and agents work on the same files in the same environment.

Faster, cheaper, better

Self-improving models, agents, and skills deliver better outcomes at scale.
Task pass rate vs. weeks since deployment. Internal F100 enterprise benchmark: same task suite, rubric-graded, 3-run mean. Each system runs its vendor's default frontier model in its shipped configuration.
40
×
Faster turnaround
28
×
Lower cost per case

Custom models trained on your work

Your team's accepted outputs become training data for models you own and serve, and they beat general-purpose agents on your specific tasks.

Evals gate every change

Rubrics and golden sets validate every runbook, model, and context change against past work before it ships. Regressions are caught automatically.

Step-level model routing

Each step routes to the cheapest model that clears your rubric. Frontier models handle only the genuinely novel, so cost falls without losing quality.

Talk to us.

Bring a workflow your team runs today and see it run in your environment.