Common Room
Also known as: CommonRoom, RoomieAI, Person360, Context360
AI native GTM intelligence platform resolving fragmented signals into complete buyer identities, with RoomieAI agents that research, prioritise and personalise outreach, delivered through Salesforce, Slack, browser extensions and MCP.
Common Room is an AI native go to market intelligence platform that resolves fragmented signals and partial identities into complete buyer pictures, then acts on them. Co founded by CEO Linda Lian, it began in community intelligence, pulling signal from Slack, Discord, GitHub and social platforms, and has since broadened into first party product and website data, CRM, marketing and engagement systems combined with third party intent. Its Person360 and Context360 layers perform identity resolution and keep enrichment current without manual maintenance.
The agent layer is branded RoomieAI and is genuinely a set of agents rather than assistive features. A capture and research agent compiles account and contact research against granular criteria, an activate agent generates personalised outreach in real time from that research, and signal, research and outreach agents run continuously. Above it sits what the company calls a Revenue Control Plane for deploying plays and governing execution across large rep populations.
The positioning worth noting is the data layer's stated purpose: buyer intelligence purpose built for consumption by language models, described as accurate enough to eliminate hallucinations and complete enough for agents to act on. That is a data quality argument aimed at agent builders rather than dashboard users, and it shapes distribution. RoomieAI agents surface inside the sales workbench, Salesforce, Slack, email, browser extensions and AI assistants, with an MCP surface extending reach to any tool where work happens.
Zoom announced on 2 July 2026 that it will acquire Common Room, citing RoomieAI agents handling account research and prospecting for customers including Atlassian, Anthropic, Autodesk, Notion, Okta and Snowflake. That is the third go to market intelligence consolidation in roughly eight months, after the Clari and Salesloft merger and Apollo's acquisition of Pocus.
Vendor details
Canonical URL
https://www.commonroom.io
Category
GTM / revenue agent
Company status
acquired
Use cases & customers
Target customers
Deployment options
In practice
Your buying signals are scattered across GitHub activity, a Slack community, product usage and website visits, and none of them resolve to the same person. Person360 and Context360 do the identity resolution so a signal becomes a named buyer at a named account.
You are building your own agents and the blocker is data quality rather than model choice. Common Room positions its buyer intelligence explicitly for language model consumption and exposes it over MCP.
Reps will not adopt another console. RoomieAI agents surface inside Salesforce, Slack, email and a browser extension so research and outreach happen where the rep already works.
Sources & related URLs
Research sources
Agentic Index coverage score
9.5 / 14 capabilities · 68%
| Integrations & Tool CallingPulls first party data from CRM, product, marketing and engagement systems and second party signal from GitHub, Slack, Discord and social platforms, and surfaces agents inside Salesforce, Slack, email and browser extensions, with an MCP surface extending reach further. 2026-08-05 | Full |
|---|---|
| Workflow OrchestrationA Revenue Control Plane deploys plays in hours and governs execution across more than a thousand reps, with agents prioritising, researching and personalising in sequence and reps actioning results in the same interface without screen switching. 2026-08-05 | Full |
| Knowledge Grounding & RAGIdentity resolution through Person360 and Context360 turns partial identities and fragmented signals into resolved people and accounts, and the company positions the resulting buyer intelligence as purpose built for language model consumption, accurate enough to eliminate hallucinations and complete enough for agents to act on. 2026-08-05 | Full |
| Human Oversight & GuardrailsGoverning execution across large rep populations is a stated capability and reps review and action agent output rather than it dispatching unattended, but no approval gates, confidence thresholds or configurable guardrail policy is documented. 2026-08-05 | Partial |
| Security, Identity & GovernanceSOC 2 compliant since April 2021 covering security, availability, processing integrity, confidentiality and privacy, with SOC 2 Type II and ISO 27001 reported alongside GDPR and CCPA compliance, data encryption and enterprise grade reliability. Data governance around person level identity resolution is a stated design focus. 2026-08-05 | Full |
| Observability & AuditabilityTransparent and adjustable scoring at both contact and account level plus dashboards give visibility into how prioritisation is derived, but no audit trail of agent actions or reasoning is documented. 2026-08-05 | Partial |
| Memory & State PersistenceContext360 maintains a continuously enriched, identity resolved buyer graph described as always current with no maintenance required, so state accumulates and stays fresh across sessions rather than being rebuilt per query. 2026-08-05 | Full |
| Deployment & Data ResidencyMulti tenant SaaS only. No self hosted, private cloud or regional data residency option is documented in any material retrieved. 2026-08-05 | Unable to verify |
| Prebuilt Agents, Templates & PacksShips named prebuilt agents rather than a build surface: a capture and research agent, an activate agent for real time personalised outreach, and signal, research and outreach agents, alongside deployable plays. 2026-08-05 | Full |
| Triggers & Channel CoverageSignal capture spans website and product first party data, GitHub, Slack, Discord and social second party activity and third party intent, and agents run continuously and surface across the workbench, Salesforce, Slack, email, browser extensions and AI assistants. 2026-08-05 | Full |
| Model Flexibility & RoutingNo model list, routing policy, model selection or bring your own key capability is documented. The company positions itself as the data layer feeding language models rather than as a model routing surface. 2026-08-05 | Unable to verify |
| APIs, SDKs & MCP ExtensibilityA first party MCP surface extends agent reach to any tool where work happens, alongside a developer surface, browser extensions and embedding inside Salesforce and Slack. The MCP claim is made on the vendor's own homepage. 2026-08-05 | Full |
| Testing, Debugging & OptimizationAdjustable transparent scoring models can be tuned against outcomes and the data layer is positioned as accurate enough to eliminate hallucinations, but that accuracy claim is unquantified and no evaluation harness, benchmark or regression testing is documented. 2026-08-05 | Partial |
| Browser & Computer UseBrowser extensions deliver agent output into the rep's workflow but do not control the browser or operate third party interfaces, matching the apollo-io precedent where a Chrome extension graded N. 2026-08-05 | Unable to verify |
The Agentic Index coverage score grades every vendor Full, Partial or Unable to verify against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded
Pricing
Not verified; third party sources report entry at either 625 or 2,100 dollars per month billed annually
seats and connected data sources
What is public
Nothing reliable. Every figure in circulation comes from competitor comparison pages that contradict each other.
Billing mechanics
Reported as tiered subscriptions scaling with seats and connected data sources, with enterprise pricing custom and higher. No first party rate card was retrieved in this pass.
Cost watchouts
Pricing reportedly scales with connected data sources as well as seats, so the bill grows as more signal systems are wired in rather than only with team size
Variable cost rationale
Cost reportedly tracks connected data sources as well as seats, so expanding signal coverage raises the bill, and with no verified rate card the exposure cannot be modelled in advance.
Additional watchouts
Independent comparisons flag limited anonymous visitor identification, a gap between signal detection and outbound execution, and a steep learning curve. The pending Zoom acquisition is the larger commercial risk for a multi year commitment.
Sales call required
Yes, required for paid access
Free / trial
Disputed: one comparison reports a free Community tier with limited features for small communities, another states there is no free tier and access is demo gated
Commercial notes
Common Room was named the preferred migration partner when Koala shut down and reportedly matched Koala's pricing tiers during that transition, which suggests real pricing flexibility in competitive situations. The Zoom acquisition announced 2 July 2026 introduces packaging uncertainty, since acquirers commonly fold standalone pricing into a wider platform bundle.
Key ambiguities
The two available sources disagree by more than three times on the entry price and contradict each other on whether a free tier exists at all. Both are competitors. Nothing here should be published without checking commonroom.io directly.
Missing data
A verified first party rate, tier names, seat minimums, whether a free tier exists, and how Zoom ownership will change packaging.
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Alternatives to Common Room
The closest documented capability profiles to Common Room among GTM and revenue agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.
- Demandbase9.0 / 14A lighter documented profile than Common Room
- ChurnZero9.5 / 14Fuller documented coverage on Human Oversight & Guardrails
- Conveyor9.5 / 14Adds documented Browser & Computer Use
- Gainsight10.5 / 14Adds documented Deployment & Data Residency
- Oliv AI9.5 / 14Fuller documented coverage on Observability & Auditability
- Salesloft8.5 / 14A lighter documented profile than Common Room
Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded