Built for operational and business teams. No setup, no code: connect your documents and tools, add your Skills, and create custom agents to execute and automate your professional workflows.
Pull the Q1 2026 sales report from @HubSpot and summarize performance by product
Tools
Web
Documents
✦ Unrestricted▤ Model’s knowledge
Cominty agents
Your agents
Sets the model for this conversation. Your agents keep their own chain and failovers.
Two things worth flagging: subscription revenue is recognised on the billing date rather than on activation, and bundles that mix a subscription with gear were split pro-rata between the subscription and store lines.
Want me to add a churn and renewal view on the subscription lines, or break the store revenue down by sport?
HubSpot✕
1
ChatGPT-5.6 Sol (Max)
GPT-5.6 Sol (Max reasoning)OpenAI
✓
Grok 4.6 (High reasoning)xAI
✓
Claude Fable 5 (XHigh)Anthropic
✓
Gemini 3.6 Pro (Max)Google DeepMind
✓
Mistral Small 4 (High)Mistral AI
✓
Kimi K3 (Max)Moonshot AI
✓
GLM 5.2 (High reasoning)Z.ai
✓
Sets the primary model for this chat. Failovers stay as they are.
Vertex-Q1-2026-Sales-by-Product.xlsxExcel · spreadsheetReadyPreviewSourceOpen in new tab
Vertex-Q1-2026-Sales-by-Product.xlsxExcel
Search cells…17 rows · 14 cols
ABCDEFGHIJKLMN
1234567891011121314151617
Q1 2026 closed-won revenue by product line
Two views of the same 78 deals. The first is exclusive and reconciles to the quarter total; the second overlaps and must never be summed.
Bundles are credited in full to both the subscription and the store line, so the overlapping view double-counts 12 deals and €92,000. That is exactly why no single-number per-product split is defensible from a HubSpot dashboard grouped on a multi-select property.
Closed-won revenue by product line (exclusive view)
By productDealsReconciliationLive from HubSpot · refreshed on sync
Same pattern for every format: docs, sheets, decks, dashboards, sites, diagrams — generated in context, versioned, and shared with a link.
03 — Four ways to work
From the easy ask to the long, complex job.
It all starts with intention. Select the mode that fits the task, or hand over the wheel and let Cominty decide — call the right agent on the spot, launch a planner to map the work with you, or kick off Hive to run long, multi-cycle tasks autonomously.
Chat. The default for everyday questions, drafts and lookups. One agent, one pass, an answer in seconds.
Hold to pause · click a mode to pin it
04 — Advanced RAG · Document intelligence
Make your enterprise documents AI-ready.
All your unstructured documents, turned into governed knowledge. Connect Drive or SharePoint in a few minutes. Every file is indexed, kept in sync, and only visible to the people who could already see it.
ComintyRetrieval pipeline — one file, end to endPermission-aware
01SourcesDrive, SharePoint and uploads, picked up as files land.sync on change
Browse a growing catalog of ready-to-use connectors built on the Model Context Protocol, or add your own by URL — we detect the authentication automatically. Every connection respects your org’s existing permissions.
Gmail
Google Drive
Stripe
Jotform
Asana
ActiveCampaign
Twilio
Todoist
Xero
PandaDoc
Netlify
Smartsheet
Linear
SurveyMonkey
PayPal
Zoho Books
SignNow
Bitly
GoCardless
Razorpay
Process Street
Semrush
Mercury
Pendo
Workable
Pylon
ZoomInfo
Guru
Gmail
Google Drive
Stripe
Jotform
Asana
ActiveCampaign
Twilio
Todoist
Xero
PandaDoc
Netlify
Smartsheet
Linear
SurveyMonkey
PayPal
Zoho Books
SignNow
Bitly
GoCardless
Razorpay
Process Street
Semrush
Mercury
Pendo
Workable
Pylon
ZoomInfo
Guru
Slack
HubSpot
Calendly
monday.com
ClickUp
MailerLite
Wix
Zoho CRM
Strava
Close
Intercom
Granola
tldv
Motion Creative Analytics
Spotify
Box
Customer.io
PagerDuty
Read AI
Base44
Grain
Cloudinary
Mixpanel
Miro
Zoho Projects
Metaview
Gamma
Databricks
Slack
HubSpot
Calendly
monday.com
ClickUp
MailerLite
Wix
Zoho CRM
Strava
Close
Intercom
Granola
tldv
Motion Creative Analytics
Spotify
Box
Customer.io
PagerDuty
Read AI
Base44
Grain
Cloudinary
Mixpanel
Miro
Zoho Projects
Metaview
Gamma
Databricks
Google Calendar
Notion
Airtable
Webflow
Shopify
Klaviyo
Fathom
Square
Quo
Docusign
Cognito Forms
Otter.ai
Attio
Apollo.io
Clay
Ticket Tailor
Krisp
Zoho Desk
NetSuite
Canva
Snowflake
PostHog
Circleback
Mem
DocuSeal
Dovetail
Egnyte
Outreach
Google Calendar
Notion
Airtable
Webflow
Shopify
Klaviyo
Fathom
Square
Quo
Docusign
Cognito Forms
Otter.ai
Attio
Apollo.io
Clay
Ticket Tailor
Krisp
Zoho Desk
NetSuite
Canva
Snowflake
PostHog
Circleback
Mem
DocuSeal
Dovetail
Egnyte
Outreach
352 live over MCP690 more on the way
01
1000+ connectors, one click
CRM, data warehouses, ticketing, monitoring, project management, internal tools — ready to connect and to act on, not just to read.
02
Organization or personal scope
Share a connection with the whole workspace or keep it to yourself; admins govern what gets shared.
03
Bring your own by URL
Point at any remote MCP server. Secrets stay in the vault, never in a prompt.
Never be locked into a single vendor’s roadmap, pricing or downtime. Cominty puts every leading model behind one control layer, so you choose the best engine for each job — and switch the moment something better, cheaper or faster arrives.
ComintyLLM router — Finance AgentRequestReconcile Q1 revenue against the closed-won pipeline
Primary modelruns every request first
Claude Opus 4.8AnthropicAnswered · 1.4sMedium
Failoverstried in order when the primary degrades
1GPT-5.6 SolOpenAIMedium
2Gemini 3.6 ProGoogle DeepMindMax
3Mistral Large 3Mistral AIStandard
+ Add failover
The request goes to Claude Opus 4.8 first, as every request does.
Model catalog120+ models, every lab, one pickerSearch models…
0Claude Opus 4.8 (Medium)Valid↑↓⌫
1GPT-5.6 Sol (Medium)Valid↑↓⌫
2Gemini 3.6 Pro (Max)Valid↑↓⌫
3Mistral Large 3 (Standard)Valid↑↓⌫
4Kimi K3 (High)Valid↑↓⌫
5GLM 5.2 (High)Valid↑↓⌫
6Claude Fable 5 (XHigh)Valid↑↓⌫
7Grok 4.6 (High)Valid↑↓⌫
8DeepSeek V4 Flash (High)Valid↑↓⌫
9Qwen 3.5 Max (Max)Valid↑↓⌫
10Llama 5 405B (Standard)Valid↑↓⌫
11Claude Haiku 4.5 (Low)Valid↑↓⌫
12 / 120+Private endpoints appear in the same list
The labs behind the picker
OpenAI
Anthropic
Google DeepMind
Mistral AI
DeepSeek
Qwen
Moonshot AI
xAI
Meta
Z.ai
NVIDIA
+ Your own endpoints
01
120+ native models
OpenAI, Anthropic, Google, Mistral, DeepSeek, Qwen, Moonshot and more, ready to use on day one.
02
Bring your own model
Connect private endpoints or custom weights over your own API — they appear in the same picker.
03
Always-on failover
Primary model first, then an ordered fallback chain, so a provider’s bad hour is never your outage.
04
Cost control
Transparency on cost per model and token usage, per agent and per member.
A skill packages instructions, scripts and know-how into a reusable unit — publish it once and it becomes available to anyone with access, official or custom.
01
Build with Skill Creator
Describe what you need in chat and let the agent draft, validate and version the skill for you.
02
Bring your own
Upload a packaged .zip or import straight from a GitHub repo with a SKILL.md.
03
Shared org-wide
Official and custom skills sit side by side, scoped by workspace or by organization.
ComintySkill lifecycle — one file, every chatReady in every chat
01Build with Skill Creator
ComintySkill Creator
Review an MSA against the Vertex contract playbook and flag liability.
02Bring your own
Upload .zip
GitHub repo
SKILL.mdlegal-review
scopeorganization
sources@SharePoint · Legal/Playbook
1.Parse the contract and map its clause structure.
2.Match each clause to the playbook in @SharePoint.
3.Flag: uncapped liability, auto-renewal beyond 12 months, one-way indemnity, notice periods over 30 days.
4.Return a .docx with a tracked comment on every flag.
v1.0 · org-wide
03Shared org-wide
/Skills picker
Cominty
Cominty
legal-reviewnew
/legal-review
Any chat · anyone with access
01Build with Skill Creator
ComintySkill Creator
Review an MSA against the Vertex contract playbook and flag liability.
02Bring your own
Upload .zip
GitHub repo
SKILL.mdlegal-review
scopeorganization
sources@SharePoint · Legal/Playbook
1.Parse the contract and map its clause structure.
2.Match each clause to the playbook in @SharePoint.
3.Flag: uncapped liability, auto-renewal beyond 12 months, one-way indemnity, notice periods over 30 days.
4.Return a .docx with a tracked comment on every flag.
Group conversations, skills, documents and integrations under one project — then hand it to a teammate, a client or a stakeholder without giving up control.
02—Secured by defaultHold to pause · click a step to replay itShared · org only02 / 03
Your workspaceFinancial dashboard12Conversations4Skills38Documents3Integrations
ONE LINKOrg only
Revoke access
A teammateSees this project onlyA clientSees this project onlyA stakeholderSees this project onlyFinancial dashboard12Conversations4Skills38Documents
Admins get a live control tower over the whole org: who is using what, which tasks dominate usage, and exactly what each model costs — down to the token.
Custom agents capture a recurring job once — a role, its instructions, the models it runs on and the exact context it works from — so anyone on your team can trigger expert-level work on demand instead of re-explaining it every time.
ComintyAgents — create one, no code· Auto-play · click to take overLive
HR
The name becomes the agent’s ID — agent::hr-scoring-agent — the one anyone picks in the composer.
Step 1 of 5
Why this step
Name it like a colleague
The name becomes the agent’s ID — the one anyone picks in the composer. The description is what your team reads before choosing it. No config files, no code.
Name
—
Instructions
—
Models
—
Context
—
You are our HR agent. Score every application against the internal hiring criteria.
Never decide on gender, age or origin — flag it and stop.
Return a score out of 100 and a two-line rationale a recruiter can act on.
3 lines · plain language, edit any time
Step 2 of 5
Why this step
Plain language, not code
Role, tone and boundaries, written the way you would brief a new hire. Refine them any time on the agent’s page — the next request uses the new version.
Name
HR Scoring Agent
Instructions
—
Models
—
Context
—
Primary model · runs every request first
Failovers · in order, if the primary degrades
2Gemini 3.6 Pro
3GPT-5.6 Sol
Step 3 of 5
Why this step
Frontier models, with failover
Claude Opus 4.8 answers first; Gemini 3.6 Pro and GPT-5.6 Sol stand by in order. If a provider degrades, Cominty retries the next one instantly — zero-downtime inference, nothing to switch by hand.
Name
HR Scoring Agent
Instructions
3 lines
Models
—
Context
—
Knowledge sources 1
Internal HR scoring methods.pdfIndexed
Tools 2
Web searchLive web results via the Cominty harness
Company documentsRetrieval from connected knowledge sources
Step 4 of 5
Why this step
The right context, at the right time
You wire the sources and tools. The harness retrieves and injects only what is relevant to each request, so the model works from the right passages instead of everything at once.
Name
HR Scoring Agent
Instructions
3 lines
Models
Claude Opus 4.8 +2
Context
—
HR
HR Scoring Agent
Classifies and scores applications against our hiring criteria.
Instructions
3 lines
Sources
1
Tools
2
Model chain
Claude Opus 4.8Gemini 3.6 ProGPT-5.6 Sol
Step 5 of 5
Why this step
One click, and it is live
Everything the agent needs is on one card. Create it, and it appears in the composer’s picker for everyone with access — with its instructions, models and context attached.
Name
HR Scoring Agent
Instructions
3 lines
Models
Claude Opus 4.8 +2
Context
2 tools · 1 sources
HR
HR Scoring Agent
Classifies and scores applications against our hiring criteria.
Instructions
3 lines
Sources
1
Tools
2
Model chain
Claude Opus 4.8Gemini 3.6 ProGPT-5.6 Sol
Step 5 of 5
Why this step
One click, and it is live
Everything the agent needs is on one card. Create it, and it appears in the composer’s picker for everyone with access — with its instructions, models and context attached.
Name
HR Scoring Agent
Instructions
3 lines
Models
Claude Opus 4.8 +2
Context
2 tools · 1 sources
HR Scoring Agent is live
In the composer’s picker for everyone with access.
In every composer
HRHR Scoring AgentScore this week’s applications
Done · no code writtenAgent created
Why this step
Built by the people who own the job
HR Scoring Agent is in the picker now. Pick it in any chat and it works from its own brief — five steps, no code, no engineer involved.
No hidden tiers, no surprises — pricing scoped to your team’s usage from day one.
ComintyYour bill, in shapeMonthly · one organization
Platform feeOne line, predictable
One predictable line for the portal, the harness, the connectors and the governance layer.
LLM budgetMetered to real usage
Matched to your real usage and steerable per agent, per team and per model.
Per-seat licenceNone
Hidden tiersNone
TotalWhat you actually use
Two lines. Both of them yours to read, steer and cap.
What that buys
100% cost transparency, down to the token
Scalable, monitorable and controllable spend
No per-seat quotes that balloon at scale
The platform fee covers the portal, the harness, the connectors and the governance layer. The LLM budget is the only line that moves — and you set how far.
The five questions that come up in every first call, answered before you have to ask them.
A Q&A bot fetches an answer; Cominty acts. It plans multi-step work and takes action across your tools — updating a CRM record, creating a ticket, drafting a follow-up from a transcript — while respecting permissions and staying traceable. If it cannot do the task, it is search, not agentic.
04
How is this different from a generic AI chatbot?
A Q&A bot fetches an answer; Cominty acts. It plans multi-step work and takes action across your tools — updating a CRM record, creating a ticket, drafting a follow-up from a transcript — while respecting permissions and staying traceable. If it cannot do the task, it is search, not agentic.
Get started
Become an AI-driven enterprise today.
Connect your tools, add your skills, and start working immediately — no setup, no code.