Enterprise AI Search That Finds Context, Not Just Keywords
Coworker uses OM1 to surface context, decisions, and expertise so people stop hunting and start acting within minutes.
saved per knowledge worker weekly
fewer repetitive questions
product velocity increase
saved per 100 employees
Enterprise AI Search Outcomes for IT and Business Leaders
Teams save eight to ten hours per week by finding critical information and action items in seconds. Coworker auto-captures and indexes conversations and documents, which frees people to focus on higher-value work instead of search and admin.
Reduce interruption and context switching by making tacit knowledge searchable. Coworker routes answers from both documented content and conversational memory so teams stop asking the same questions and get consistent results.
Productivity improves when decisions and historical context are available at search. Expect measurable velocity gains as teams use organizational memory to run faster and avoid rework across projects, which improves delivery timelines and outcomes.
Maintain existing access controls while exposing context where appropriate. Coworker is SOC 2 Type 2 and GDPR compliant, so security and governance stay tightly controlled while data becomes more useful to the right people.
How OM1 Powers Contextual Enterprise Search
OM1 builds a synthesized memory layer across projects, roles, and conversations. That means search returns answers informed by relationships, past decisions, and team priorities rather than only matching keywords.
Coworker connects Slack, Teams, Google Workspace, GitHub, Jira, Notion, Confluence and more to create a single search surface. Indexing is granular so you find the exact message, document, or code snippet tied to a decision or action item.
Ask real questions in plain language and get answers with context and source links. Coworker ranks results by relevance to your role and project context so the first result is often the one you need.
The system adapts as people change roles and projects shift. Coworker tracks organizational signals over time so results reflect current priorities and historical reasoning, keeping search aligned with reality.
Enterprise AI Search Use Cases for Cross-Functional Teams
Reduce support load by making answers searchable across conversations and docs. Coworker surfaces existing explanations and decision notes so teams find answers without interrupting subject matter experts.
Automatically capture decisions, action items, and rationale from meetings and code reviews. That makes institutional knowledge explicit without forcing engineers or managers to write formal docs after every session.
Coworker links related tickets, documents, and conversations to show the full context behind a task. That reduces missed handoffs and keeps cross-functional work aligned with strategic priorities.
Track action items and the reasoning behind decisions so follow-through is visible. Coworker ties meeting outputs to projects and stakeholders so information stays actionable and traceable.
Security And Integrations For Enterprise Search
Coworker is SOC 2 Type 2 and GDPR compliant and operates without elevating permissions. That preserves your access model while making organizational memory searchable under existing controls.
Coworker enhances your existing platforms rather than replacing them. Connectors index data across tools so you retain functional systems while gaining cross-tool context and intelligence.
Access is granted according to your permissions and every query can be audited. That keeps sensitive information protected while providing teams the context they need.
Over 50 apps supported with near real-time sync so results reflect current conversations and documents. Fresh indexing ensures the answers you get match what people are working on today.
Connects to your entire stack
100+ OAuth connectors. Permissioned and secure. Your agents work across every tool your team already uses.
Proof Points And ROI From Enterprise Search
Customers report 60 percent less time spent searching and 14 percent faster project velocity after adopting Coworker. For a 100-person team, this can translate to roughly $750,000 in annual savings through reduced duplication and faster decisions.
Teams describe Coworker as a core part of daily workflows because it surfaces critical context and missed information.
Before, teams hunt across Slack, docs, and tickets. After, a single search returns the right message, document, and decision history in one view which reduces missed context and accelerates execution.
Coworker's approach to organizational memory and cross-functional synthesis is distinct from naive RAG systems. OM1 builds a layered context that analysts and enterprise buyers recognize as essential for reliable results.
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Learn moreFAQ
Frequently asked questions
Enterprise AI Search uses context, roles, and organizational memory to return meaningful answers rather than matching keywords. Coworker's OM1 synthesizes conversations, documents, and project data so results include decisions and who knows what.
Coworker respects your existing permissions and does not elevate access. Search results are filtered by the same rules your systems use, and all queries can be audited to ensure governance and compliance are maintained.
Coworker connects to over 50 apps including Slack, Teams, Google Workspace, GitHub, and Jira. Sync frequencies are configurable so search results reflect recent conversations and documents relevant to ongoing work.
Initial value appears within days when priority apps are indexed and core teams use search. Early wins come from deflecting repetitive questions and surfacing meeting action items which reduces friction immediately.
Yes. OM1 auto-captures and contextualizes meeting notes, decisions, and action items. That makes tacit knowledge discoverable without requiring manual documentation from experts.
Enterprises commonly report 60 percent less time searching and up to $750,000 saved per 100 employees through reduced duplication and faster decisions. Results vary by usage but early pilots typically show clear time savings.
Coworker complements rather than replaces existing platforms. It indexes and synthesizes data from your tools so those systems retain their workflows while gaining organizational intelligence for better decisions.
Coworker is SOC 2 Type 2 and GDPR compliant and follows enterprise-grade controls. Implementation respects your audit and permission requirements so security teams can approve deployment with confidence.
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