Work

Answers, Analysis, Action

One AI that reads, writes, and acts across all your tools, and turns any answer into a finished deliverable: documents, decks, dashboards, and code, grounded in your live company data.

Coworker

app.coworker.ai
Who owns the Acme renewal? Flag anything at-risk and post to #enterprise-renewals.

Trusted by

RapidSOSHuuuge GamesSafetyWingCortexColumn
cheaper with OM2
9x
cheaper with OM2
cheaper with OM2 + model routing
51x
cheaper with OM2 + model routing
better quality
84.5%
better quality
connectors, permission-aware
50+
connectors, permission-aware

Statistically significant benchmarks comparing Coworker MCP vs. Claude Native Tooling. See the methodology

Key features

Ask it, have it done, get the finished work

Grounded chat

Better answers, no prompt engineering

Conversations run against your org's connected data, so answers are relevant and trustworthy out of the box.

Artifacts / Canvas

Chat becomes finished work

Decks, docs, and dashboards are produced and editable, not just text replies.

CoDrive

Work is shared, not siloed

Folders, shared drives, and an inbox for artifacts, agents, and meetings mean good work gets discovered and reused.

Coworker Platform

OM2 + smart model routing

Org memory and the right model for every task cut token spend while improving quality and speed.

Work for every role.

Pick a team. Watch it work across your tools, reason through the request, and act with your approval.

Artifacts

What you can build

Every artifact pulls from your connected company data instead of a hypothetical prompt. Point Coworker at Salesforce, your sheets, or your warehouse and get back something real, not a mockup.

Salesforce
Michael's Salesforce Pipeline
Refreshable · Live Salesforce data
Refreshed just now
Active pipeline
$4.24M
+8.2%
Deals won (QTD)
$1.68M
+12.4%
Deals lost (QTD)
16
−3
Win rate
51%
+4 pts
Pipeline by stage
QTD · 29 open deals
Qualification$1.84M · 8 deals
Proposal$1.32M · 5 deals
Negotiation$0.72M · 4 deals
Closed Won$1.68M · 12 deals
Weekly bookings trend
$2.03M · last 8 weeks
W1W2W3W4W5W6W7W8$365K
Top open deals
By amount
AccountStageAmountOwnerClose
StripeNegotiation$320KMichael K.Apr 28
DatadogProposal$280KLisa T.May 12
NotionQualification$245KMichael K.May 30
VercelNegotiation$180KLisa T.Apr 22
FigmaProposal$165KLisa T.May 18
BrexQualification$140KMichael K.Jun 04
Recently closed won
Past 14 days
Linear$385KApr 14
Asana$310KApr 09
Mercury$220KApr 02

Dashboard

See it before you build it.

A live dashboard, wired to your data, generated from one prompt.

A
B
C
D
E
F
G
H
I
J
K
L
M
N
1
Income Statement (Monthly)
2
3
Line item
Units
M0
M1
M2
M3
M4
M5
M6
M9
M12
M18
M24
M36
4
ARR ROLLFORWARD
5
Beginning ARR
$
0
10.0M
10.2M
10.5M
10.7M
11.0M
11.2M
12.0M
12.8M
14.8M
17.0M
23.0M
6
New Logo ARR
$
0
250k
263k
276k
290k
304k
319k
369k
427k
575k
773k
1.4M
7
Expansion ARR
$
0
80k
82k
84k
86k
88k
90k
96k
103k
118k
136k
184k
8
Churn ARR
$
0
-100k
-102k
-105k
-107k
-110k
-112k
-120k
-129k
-148k
-170k
-230k
9
Ending ARR
$
0
10.2M
10.5M
10.7M
11.0M
11.2M
11.5M
12.3M
13.2M
15.1M
17.4M
23.5M
10
11
REVENUE & GROSS PROFIT
12
Revenue
$
0
853k
872k
892k
913k
934k
956k
1.0M
1.1M
1.3M
1.5M
2.0M
13
Gross Margin %
%
—
72.0%
72.2%
72.4%
72.6%
72.8%
73.0%
73.5%
74.0%
75.5%
77.0%
80.0%
14
Gross Profit
$
0
614k
630k
646k
663k
680k
698k
752k
811k
952k
1.1M
1.6M
15
16
OPERATING EXPENSES
17
R&D (incl. payroll)
$
0
213k
218k
223k
228k
234k
239k
256k
274k
315k
363k
490k
18
S&M (incl. payroll)
$
0
298k
305k
312k
320k
327k
335k
358k
384k
441k
508k
685k
19
G&A (incl. payroll)
$
0
102k
105k
107k
110k
112k
115k
123k
132k
151k
174k
235k
20
Total OpEx
$
0
614k
628k
642k
657k
673k
688k
737k
789k
908k
1.0M
1.4M
21
22
PROFITABILITY
23
EBITDA
$
0
0
2k
4k
5k
7k
10k
15k
22k
44k
73k
157k
24
Net Income (Loss)
$
-50k
-50k
-48k
-46k
-45k
-43k
-40k
-35k
-28k
-6k
23k
107k
Assumptions
P&L
Balance Sheet
Charts

Spreadsheet

Numbers you can trust.

Every row and every formula real, a working spreadsheet built from a prompt.

Coworker.ai logo
Sales Discovery Follow-Up

Same spend, 5x more AI

The enterprise AI platform that connects 50+ tools, delivers 5x the output for the same token spend, and never trains on your data.

Coworker.ai × Stripe Partnership Overview
May 2026
Prepared forStripe

Document / PDF

Ready to send, not just ready to read.

A formatted brief, laid out and polished, straight from a prompt.

Vanta
Confidential
Quarterly Board Update
Q2 2026: Pipeline, Financials & Strategic Priorities
Prepared for: Board of Directors
May 2026

Slide deck

A deck that sources its own numbers.

Slides built from your connected data, not a blank template.

Model routing cost
$0.15/ 1M input tokens
↓ 99% vs. GPT 6 Astra

Interactive app

Not a mockup. Running code.

An interactive calculator, built and working, from a single prompt.

IR
Infosec Questionnaire Responder
Reactive agent · Slack-triggered · Draft → review → submit
Live

Identity

How this agent appears to the team.

Name
Infosec Questionnaire Responder
Description
Drafts answers to vendor security questionnaires posted in #infosec-responses.

Triggers

What kicks this agent off.

Slack: new message
Reactive
Channel#infosec-responses
MatchAny message with attachment, link, or “questionnaire”
Debounce30 seconds

Instructions

Plain-English description of what the agent should do, every time.

You are Vanta's Infosec Questionnaire Responder. When a new questionnaire is posted in #infosec-responses: 1. Parse questions from the message, attachment, or linked Google Form. 2. Search the security wiki (Notion), policy library (Confluence), and SOC 2 evidence (Drive) for grounded answers. 3. Draft each response with the source linked inline. Flag low-confidence items (<80%) for human review. 4. Post the draft as a threaded reply with Approve / Edit / Reject buttons. Wait for human approval before submitting. Never invent control statements. Always cite the source doc.

Data sources & tools

What the agent can read from and write to. Permissions inherit from your account.

Slack
ReadWrite
Notion (Security Wiki)
Read
Confluence (Policies)
Read
Google Drive (SOC 2 evidence)
Read

Guardrails

When the agent should pause and ask a human.

Require human approval before posting
Confidence threshold to draft
80%
Auto-approve when confidence ≥ 95%
Max questionnaire size
50 questions
Credit limit per run
50,000 tokens

Notifications

Where outputs and alerts go.

Post drafts to
#infosec-responses · thread
Notify on approval
@michael.kim
Alert on low-confidence answers
Weekly summary
Mondays at 9:00 AM ET

Agent

Describe the job. It runs itself.

Triggers, data access, and guardrails. Configured, not coded.

Salesforce
Michael's Salesforce Pipeline
Refreshable · Live Salesforce data
Refreshed just now
Active pipeline
$4.24M
+8.2%
Deals won (QTD)
$1.68M
+12.4%
Deals lost (QTD)
16
−3
Win rate
51%
+4 pts
Pipeline by stage
QTD · 29 open deals
Qualification$1.84M · 8 deals
Proposal$1.32M · 5 deals
Negotiation$0.72M · 4 deals
Closed Won$1.68M · 12 deals
Weekly bookings trend
$2.03M · last 8 weeks
W1W2W3W4W5W6W7W8$365K
Top open deals
By amount
AccountStageAmountOwnerClose
StripeNegotiation$320KMichael K.Apr 28
DatadogProposal$280KLisa T.May 12
NotionQualification$245KMichael K.May 30
VercelNegotiation$180KLisa T.Apr 22
FigmaProposal$165KLisa T.May 18
BrexQualification$140KMichael K.Jun 04
Recently closed won
Past 14 days
Linear$385KApr 14
Asana$310KApr 09
Mercury$220KApr 02

Dashboard

See it before you build it.

A live dashboard, wired to your data, generated from one prompt.

A
B
C
D
E
F
G
H
I
J
K
L
M
N
1
Income Statement (Monthly)
2
3
Line item
Units
M0
M1
M2
M3
M4
M5
M6
M9
M12
M18
M24
M36
4
ARR ROLLFORWARD
5
Beginning ARR
$
0
10.0M
10.2M
10.5M
10.7M
11.0M
11.2M
12.0M
12.8M
14.8M
17.0M
23.0M
6
New Logo ARR
$
0
250k
263k
276k
290k
304k
319k
369k
427k
575k
773k
1.4M
7
Expansion ARR
$
0
80k
82k
84k
86k
88k
90k
96k
103k
118k
136k
184k
8
Churn ARR
$
0
-100k
-102k
-105k
-107k
-110k
-112k
-120k
-129k
-148k
-170k
-230k
9
Ending ARR
$
0
10.2M
10.5M
10.7M
11.0M
11.2M
11.5M
12.3M
13.2M
15.1M
17.4M
23.5M
10
11
REVENUE & GROSS PROFIT
12
Revenue
$
0
853k
872k
892k
913k
934k
956k
1.0M
1.1M
1.3M
1.5M
2.0M
13
Gross Margin %
%
—
72.0%
72.2%
72.4%
72.6%
72.8%
73.0%
73.5%
74.0%
75.5%
77.0%
80.0%
14
Gross Profit
$
0
614k
630k
646k
663k
680k
698k
752k
811k
952k
1.1M
1.6M
15
16
OPERATING EXPENSES
17
R&D (incl. payroll)
$
0
213k
218k
223k
228k
234k
239k
256k
274k
315k
363k
490k
18
S&M (incl. payroll)
$
0
298k
305k
312k
320k
327k
335k
358k
384k
441k
508k
685k
19
G&A (incl. payroll)
$
0
102k
105k
107k
110k
112k
115k
123k
132k
151k
174k
235k
20
Total OpEx
$
0
614k
628k
642k
657k
673k
688k
737k
789k
908k
1.0M
1.4M
21
22
PROFITABILITY
23
EBITDA
$
0
0
2k
4k
5k
7k
10k
15k
22k
44k
73k
157k
24
Net Income (Loss)
$
-50k
-50k
-48k
-46k
-45k
-43k
-40k
-35k
-28k
-6k
23k
107k
Assumptions
P&L
Balance Sheet
Charts

Spreadsheet

Numbers you can trust.

Every row and every formula real, a working spreadsheet built from a prompt.

Coworker.ai logo
Sales Discovery Follow-Up

Same spend, 5x more AI

The enterprise AI platform that connects 50+ tools, delivers 5x the output for the same token spend, and never trains on your data.

Coworker.ai × Stripe Partnership Overview
May 2026
Prepared forStripe

Document / PDF

Ready to send, not just ready to read.

A formatted brief, laid out and polished, straight from a prompt.

Vanta
Confidential
Quarterly Board Update
Q2 2026: Pipeline, Financials & Strategic Priorities
Prepared for: Board of Directors
May 2026

Slide deck

A deck that sources its own numbers.

Slides built from your connected data, not a blank template.

Model routing cost
$0.15/ 1M input tokens
↓ 99% vs. GPT 6 Astra

Interactive app

Not a mockup. Running code.

An interactive calculator, built and working, from a single prompt.

IR
Infosec Questionnaire Responder
Reactive agent · Slack-triggered · Draft → review → submit
Live

Identity

How this agent appears to the team.

Name
Infosec Questionnaire Responder
Description
Drafts answers to vendor security questionnaires posted in #infosec-responses.

Triggers

What kicks this agent off.

Slack: new message
Reactive
Channel#infosec-responses
MatchAny message with attachment, link, or “questionnaire”
Debounce30 seconds

Instructions

Plain-English description of what the agent should do, every time.

You are Vanta's Infosec Questionnaire Responder. When a new questionnaire is posted in #infosec-responses: 1. Parse questions from the message, attachment, or linked Google Form. 2. Search the security wiki (Notion), policy library (Confluence), and SOC 2 evidence (Drive) for grounded answers. 3. Draft each response with the source linked inline. Flag low-confidence items (<80%) for human review. 4. Post the draft as a threaded reply with Approve / Edit / Reject buttons. Wait for human approval before submitting. Never invent control statements. Always cite the source doc.

Data sources & tools

What the agent can read from and write to. Permissions inherit from your account.

Slack
ReadWrite
Notion (Security Wiki)
Read
Confluence (Policies)
Read
Google Drive (SOC 2 evidence)
Read

Guardrails

When the agent should pause and ask a human.

Require human approval before posting
Confidence threshold to draft
80%
Auto-approve when confidence ≥ 95%
Max questionnaire size
50 questions
Credit limit per run
50,000 tokens

Notifications

Where outputs and alerts go.

Post drafts to
#infosec-responses · thread
Notify on approval
@michael.kim
Alert on low-confidence answers
Weekly summary
Mondays at 9:00 AM ET

Agent

Describe the job. It runs itself.

Triggers, data access, and guardrails. Configured, not coded.

These are just the ones people reach for most. Describe anything else and Coworker builds it, grounded in your data.

The ROI calculation was straightforward. We just needed to save two to two and a half hours per month per person to break even. We exceeded that in the first few weeks.

Marcin Safranow

Marcin Safranow

VP IT Operations, Huuuge Games

Huuuge Games
Powered by the Coworker Platform / OM2

Every model needs the right context.

OM2 captures both your individual context and your whole team’s, in one knowledge graph. Customers, projects, decisions, workflows, and what you personally work on, pre-loaded before every task. Learns continuously, gets smarter every day.

customer14s ago

Mosaic Financial

Series B fintech · $3.1M ARR · 47 seats

24linked
12sources
0.8ssynth
SOC 2 Type II auditPriya NambiarEnterprise onboardingCustomer Success#mosaic-impl
LiveOnboarding kickoff call with Priyavia Gong
Model routing

The right model for every task, automatically.

Coworker routes each task to the optimal model across closed, open-source, and self-hosted providers, cutting AI spend without cutting quality.

How model routing works

5 model providers

Anthropic, OpenAI, and Google, plus open-weight models from Moonshot and Z.ai.

Lower cost, same quality

Every task routed to the cheapest model that meets the quality bar, with OM2 pre-narrowing context.

BYOM supported

Bring your own models on your own infrastructure.

5 providers · 13 models

AnthropicOpenAIGoogleMoonshotZ.ai
How it works

Talk to your company context. Get real output. In minutes.

01

Connect your tools

50+ OAuth connectors, permissioned and secure: Slack, Google, Microsoft 365, Jira, HubSpot, Salesforce, and more.

50+
See all connectors
02

Coworker learns context

Reads messages, tickets, deals, docs, sheets, calendars, and more, then understands style, workflows, and how to execute.

MessagesTicketsDealsDocsMeetingsCode
03

Start asking, or start building

Ask questions and get sourced answers, or describe a deliverable and watch Work generate it from your real data.

Who owns the Acme renewal?Sales
Summarize Q1 campaign resultsMarketing
Draft a Q4 board deck from our pipeline dataRevenue
Security and governance

Enterprise-grade security, from day one

SOC 2 Type II

Audited annually, report on request

Hosted locally

Your memory stays in your region. Open-source models run in the US.

Isolated per company

In our cloud or your VPC

Never trains on your data

No model provider, closed or open source

Your permissions, enforced

The access already set in Salesforce, Slack, Jira and Drive

Also included

GDPRCASA Tier 2Node-level permissions at query timeEvery fact traceable to its sourceSSO and SAMLAES-256 at rest, TLS 1.2+ in transitRegional data residency
Context Impact Report

See the numbers on your own data, free.

Our app runs the benchmark on your own systems, we cover the token costs, and you keep the numbers whichever way they land.

Get your free Context Impact Report

Your part: two steps

  • Sign an NDA and tell us which systems to cover.
  • Name one or two testers to install the Coworker benchmarking app.

Our part: everything else

Connect your sources, build your graph, run the question set against your current setup and through Coworker, score every answer blind, then tune and run it again.

FAQ

Frequently asked questions

Coworker's conversational AI and work-product engine in one: ask anything across your connected tools for grounded, sourced answers, or describe a deliverable and get a real, editable work product, generated from your prompt and your company data in seconds.

Coworker is connected to your actual company data and tools. It doesn't just answer questions, it can create Jira tickets, update Salesforce, send Slack messages, and draft documents through natural language. It also learns your organization's context over time, getting more accurate with every interaction.

Coworker natively connects to 50+ tools including Salesforce, HubSpot, Slack, Microsoft Teams, Jira, Linear, Google Drive, Notion, Confluence, Gong, Zoom, Snowflake, and more. It can read, write, and act across all connected sources.

Both. Coworker can answer questions grounded in your company data and also execute actions: create tickets, update CRM records, send messages, draft documents, all through natural language, pending your approval.

Yes. Artifacts is Coworker's dedicated work-product engine: turn any conversation into a branded doc, deck, spreadsheet, model, or dashboard, grounded in your real data. Visit the Artifacts page for the full catalog and examples.

No. Coworker never trains on your company data.

Ask for a free Context Impact Report. Your side is two steps: sign an NDA and name one or two testers to install the Coworker benchmarking app. We connect your sources, build OM2 on your data, run the question set against your current setup and through Coworker, score every answer blind, and cover the token costs. You keep the numbers either way.

Coworker is typically live within minutes of connecting your first tool. Full organizational setup with OM2 memory is scoped collaboratively, and enterprise customers get a dedicated onboarding team to guide rollout.

See what happens when AI knows your business and does the work.

Book a 20-minute demo, or get a free benchmark of Coworker on your own company's data.