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Trusted by teams at
FPL logoStripe logoPalantir logoItaú logo

Context, execution, identity, and evals on one foundation.
Everything agents need to work in production.

Modules for every role, tool, and use case.

Workspace

Workspace screenshot
Plain-English workflows anyone can author
Same surface for your team and your agents
Full audit on every run

Engine

Engine screenshot
Identity inherited from your IdP at every action
800+ connectors to the tools your team uses
Hosted, in your VPC, on-prem, or air-gapped

Unify

Unify screenshot
Your firm's knowledge available to every agent
Agents capture what they learn for the next run
Permissions follow each user's grants

Evals

Evals screenshot
Rubrics ensure agent quality at every run
Accepted outputs become reusable standards
Routing improves automatically as the library grows

One platform for people and agents.

Chat, files, tasks, skills, applets and evals in one product, shared by your team and the agents that work with it.

q3-portfolio-reviewThursday's review: updates, bridge, deck, covenant watch7
Messages FilesDetails
Today
Maya Okafor09:02

Review is Thursday. Priya, can you get the portfolio pack started? Same structure as Q2, and Northwind and Alder go in the risk section this time.

Priya Natarajan09:04

@Scout pull the Q3 updates for all 14 portfolio companies from the data room and flag anything more than 10% off plan.

Scout09:04
Q3 portfolio updates
Done in 6 min 12 s
Wrote q3-portfolio-updates.docx, 184 KB
q3-portfolio-updates.docxworkspaces/b/q3-portfolio-reviewDoc · 184 KB

Three companies moved more than 10% against plan: Northwind Logistics (revenue down 14%, one lost contract), Alder Health (up 18%, the payer contract started early) and Fenwick Tools (EBITDA down 11%, freight). Sources are linked in the doc.

2
Marco Vitale09:12

@Ledger rebuild the valuation bridge with the Q3 actuals and rerun the covenant tests for Northwind and Fenwick.

Ledger09:13
Q3 valuation bridge
Done in 4 min 40 s
Wrote q3-valuation-bridge.xlsx, 612 KB
q3-valuation-bridge.xlsxworkspaces/b/q3-portfolio-reviewSheet · 612 KB

Northwind passes leverage at 3.9x against a 4.5x covenant. Fenwick's interest cover is 2.1x with the test at 2.0x: passing, but tight. One tab per company in the workbook.

Send a message in #q3-portfolio-review
  1. 01

    Work together

    Ask for the deck in the team channel. Atlas, the team's analyst agent, reads the updates and the bridge, builds the slides, and the file lands in the thread when it is done.

  2. 02

    Turn work into apps

    Ask Ledger, the finance agent, to keep the covenant numbers where everyone can watch them. It builds an applet from the workbook, and the applet opens beside the channel.

  3. 03

    Codify what works

    Atlas, the analyst agent, built the deck from a skill: steps you can read and edit. Share the skill with the workspace and every agent follows the same steps.

  4. 04

    Make it better every week

    Every run is scored against your criteria. A failed criterion goes to the Improver, which writes a new version of the skill from that feedback, so the agents get better, cheaper and faster every week.

  5. 05

    Any model, always improving

    Pick the model each agent runs on. The skills, scorecards and improvements stay, so the work keeps getting better whichever model you choose.

Product updates and engineering notes

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.

Continuously improve with every layer of context your team adds.

$20094%task-completion accuracy
23%$7compute cost per case
Raw agent
Off the shelf
A frontier model with no context. Where it stays, frozen at deployment.
+ Domain documents
The “what”
Facts, files, and relationships. Necessary, not sufficient.
+ Plain-English runbooks
The “how”
Procedures, approvals, and the order work actually happens in.
+ Rubrics and golden sets
Your standard
Your team's definition of good, captured and held to.
Production workflows running on the same base model at every stage.

Own your intelligence with infrastructure you control.

Codex and Cowork route every task to one lab's frontier models, in the lab's cloud. Vertical tools lock you to a single interface. Context is the execution layer you run: on your compute, across any model, with the learning loop staying yours.

Context compared with Codex, Cowork, and vertical AI tools
Enterprise permissioning
Context
Agents inherit each user's permissions from your IdP. Every action is authorized before it touches data.
Codex
Scoped to a provider account
Cowork
Scoped to a provider account
Vertical tools
Per-app roles on one surface
Model choice
Context
Any model. Claude, GPT, Gemini, Kimi, or open weights, whichever wins the task.
Codex
OpenAI models only
Cowork
Anthropic models only
Vertical tools
The vendor's fixed stack
Cost over time
Context
Accepted work distills into cheaper models you own. Metered in CCUs, decoupled from any model vendor.
Codex
Frontier inference, cost scales with use
Cowork
Frontier inference, cost scales with use
Vertical tools
Flat per seat or per query
Deployment
Context
Your VPC, on-prem appliance, or air-gapped. Compute and identity stay on your side.
Codex
Provider's multi-tenant cloud
Cowork
Provider's multi-tenant cloud
Vertical tools
Multi-tenant SaaS
Agent choice
Context
Run any agent or framework on the platform, not a single vendor's.
Codex
One vendor agent
Cowork
One vendor agent
Vertical tools
A closed, fixed workflow
Internal systems and retrieval
Context
800+ permissioned connectors and an institutional-context engine grounding every run.
Codex
A handful of connectors
Cowork
A handful of connectors
Vertical tools
Source connectors for one domain
Humans and agents together
Context
People and agents share one environment, filesystem, and deliverables.
Codex
A solo coding agent
Cowork
An assistant surface
Vertical tools
Single-user chat
Evaluation suite
Context
Rubrics, golden sets, and dashboards built in. Every run scored automatically.
Codex
None built in
Cowork
None built in
Vertical tools
None built in
Data ownership
Context
Traces, rubrics, and tuned models stay in your perimeter. You own them.
Codex
Flows to the model provider
Cowork
Flows to the model provider
Vertical tools
Locked inside the vendor

Models, frameworks, and vendors change. The platform you run, and the data your team generates inside it, stays with you.

Built for the work in your industry.

Prebuilt agents for industry-specific workflows, systems, and controls.

Connects to the tools you already use

Connect a source once. Agents read, work, and write back under the access rules you set.

800+ connectors across data warehouses, documents, CRMs, ticketing, and internal systems.

Browse all connectors →

Data and warehouses

SnowflakeDatabricksBigQueryPostgresLooker

Documents and knowledge

BoxNotionConfluenceGoogle Drive

CRM and support

SalesforceHubSpotZendeskServiceNow

Engineering and communication

JiraGitHubSlackMS Teams

and hundreds more, across 18 categories

Some of the agents built on these connections

Due diligenceReads the full data room and extracts what mattersBoxSnowflakeNotionChip designTracks RTL-to-GDSII progress across blocks and flags critical-path slipsGitHubJiraSlackWorkflow automationAutomates handoffs across teams and toolsServiceNowSlackAsana
See all 78 agents →

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