Native Shared Memory
Computer’s Native Shared Memory is described as a knowledge graph that lets the platform reason across live product, support, and sales data instead of stale snapshots.
Plateforme native IA pour la recherche, l’automatisation et les workflows d’agents sur les données produit, support et ventes
DevRev’s Computer is an AI-native platform built around Native Shared Memory, which it describes as a way to reason across live product, support, and sales data. The product is positioned for teams that need search, automation, and contextual answers from the same shared data layer rather than from separate tools.
The site presents Computer as a platform for multiple teams, including customer support, sales, enterprise search, service desk automation, and operations. Agent Studio extends that platform with a no-code environment for building agents that can test, deploy, and optimize workflows while keeping human oversight and guardrails available for higher-risk actions.
Pricing is organized into Mini, Pro, and Max plans. Mini is free, Pro and Max use contact-sales pricing, and the higher tiers add broader connectors, Agent Studio, custom connectors, applied AI support, and enterprise security and sync options.
Computer’s Native Shared Memory is described as a knowledge graph that lets the platform reason across live product, support, and sales data instead of stale snapshots.
The platform includes a conversational interface on desktop, mobile, and browser so teams can search, act, and automate from multiple surfaces.
Mini includes accurate search across organizational data and basic task automation, while the broader platform supports contextual answers and conversational analytics on higher plans.
Agent Studio lets teams describe an agent in plain language, then test, deploy, and optimize it without code, with optional human review before actions are taken.
Agents can be deployed across channels such as email, Slack, and WhatsApp, and they can create tickets, resolve repetitive questions, and update CRM records.
The pricing page lists one-click connectors, a connectors marketplace with hundreds of integrations and snap-ins, and custom connectors for enterprise setups.
Use Computer to reduce ticket backlog by connecting current tickets, past resolutions, and your knowledge base, then routing or resolving cases with the right context.
Use the platform to prep meetings, summarize pipeline status, and update CRM records so sales teams spend less time on admin work.
Use Computer for enterprise search when you need answers from live organizational data rather than static snapshots or guesswork.
Use the service desk agent to answer common IT questions, resolve issues, and keep employees productive around the clock.
Use Agent Studio to build and deploy agents that create tickets, handle repetitive questions, and update records across channels like email, Slack, and WhatsApp.
Computer is positioned as an AI-native platform that reasons across live product, support, and sales data using Native Shared Memory. Agent Studio is the no-code environment for building agents that can take action.
The source shows desktop app, mobile app, and browser access, plus deployment across channels such as email, Slack, and WhatsApp for agents built in Agent Studio.
The pricing page shows a free Mini plan, contact-us Pro and Max plans, and paid credits based on consumption. Pro adds Agent Studio and a broader connectors marketplace; Max adds custom connectors, embedded applied AI support, and enterprise security features such as SCIM.
Computer can use one-click connectors, a connectors marketplace with hundreds of integrations and snap-ins, and custom connectors on higher plans. The source specifically mentions Slack, Notion, Jira Cloud, Google Drive, Calendar, Microsoft Teams, OneDrive, and SharePoint.
The source describes Computer as reasoning across live data rather than stale snapshots, and Agent Studio includes sandbox testing, automatic versioning, human approval for high-stakes actions, guardrails, and decision logs. Those controls indicate the platform is designed for controlled deployment rather than fully unattended experimentation.
Les données de trafic sont fournies à titre indicatif uniquement.
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