The problem: context is broken
Organizations run 50+ disconnected tools across Engineering, Sales, Support, Finance, IT/HR, and Product. People, process, and data live in silos with zero shared truth. Teams build fragile point-to-point integrations that move data but destroy context.
DevRev unifies this fragmented landscape into a single context layer - connecting every tool, preserving every relationship, and making it all accessible through AI that respects permissions at the vector level.
AirSync - two-way sync, infinite memory
Not another point-to-point connector. AirSync implements schema-aware, bidirectional transformation that preserves full context.
- Real-time bidirectional sync across 50+ enterprise tools.
- Full historical migration - millions of records, lossless, with attachments, comments, custom fields, and audit trails intact.
- Schema-aware transformation - understands relationships between objects, not just flat field mappings.
- Incremental sync - only moves deltas after initial load, keeping systems in lock-step.
Permission-aware vectors
DevRev embeds access controls directly into vector embeddings. The system reads each source's permissions and fuses them into the vector itself - one AI assistant serving every user while enforcing individual access levels at retrieval time.
VP of Engineering asks about a production incident. The system retrieves full context including root cause from internal post-mortems, linked code changes, and customer impact data - all of which their role has access to.
Same question from a customer-facing rep. The system provides ticket status and resolution ETA, but withholds internal post-mortem details, code-level root cause, and financial impact metrics their role doesn't have access to.
No additional configuration. No separate permission layers. Access is intrinsic to the data itself.
Knowledge graph
Every object - tickets, opportunities, incidents, contacts, code commits, articles - connected in a single traversable graph with full relationship context.
- Connects 50+ tools across every department.
- Links standard objects with custom objects and external data.
- Enables multi-hop traversal across the entire relationship landscape.
- Temporal snapshots for trend analysis and point-in-time queries.
- Context engineering as infrastructure, not a feature bolt-on.
Search - three methods, one interface
Syntactic
Field-level precision. Exact matches, filters, and structured queries across every connected data source.
Semantic
Meaning-based retrieval across unstructured content - documents, conversations, transcripts, articles.
Text-to-SQL
Natural language translated to precise database queries. No LLM overhead when you don't need it.
Syntactic queries bypass LLMs entirely - AI is only invoked where meaning-based reasoning is required. This is precision, not brute force.
Computer - AI agent
An AI teammate with native shared memory across your entire organizational data. Not a chatbot - an agent that acts.
- Shared memory - Remembers context across conversations, users, and sessions.
- Multiplayer sessions - Multiple people collaborating with the same agent in real time.
- Private mode - Senior users can restrict visibility of sensitive data from collaborators within the same session.
- Cross-platform - Desktop, mobile, web, Slack, Gmail, CRM - wherever work happens.
- Inline analytics - Generates charts, tables, and visualizations on the fly, exportable as HTML, PDF, or PPT.
Customer-facing surfaces
AI-powered interfaces deployed wherever your customers are.
Chat widget
In-product AI assistance that draws from your full knowledge graph - articles, past tickets, product docs - to resolve issues instantly.
Search bar
Embedded contextual search delivering instant answers from your knowledge base without leaving the product.
Customer portal
Self-serve support hub where customers find answers, track tickets, and access documentation - reducing inbound volume.
Voice AI
Phone-based AI agent handling customer calls with full context awareness and seamless handoff to humans when needed.
Grow - sales intelligence
Full pipeline and account 360 views powered by the knowledge graph - not just CRM data, but every touchpoint across every connected system.
- Account 360 with unified context from support, product, and engineering.
- Pipeline management with AI-driven deal insights.
- Automated meeting prep and post-call action items.
- Revenue intelligence drawing from every customer interaction.
Workflow engine
Three abstraction layers - choose the one that matches your team's skill set.
Snap-In Code
TypeScript SDK for engineers who need full programmatic control over automation logic.
Drag & Drop
Visual workflow builder for operations teams. No code, full power.
AI Agent Skill
Describe what you want in plain language. The agent builds and executes the workflow.
Extensibility & marketplace
- AirSync connectors - Deep bidirectional sync with full schema awareness. Data lives in your knowledge graph.
- MCPs (Model Context Protocol) - Real-time tool calls to external systems without storing data. Ephemeral context on demand.
- Deployment options - Public marketplace for shared connectors, or private org-only deployment for proprietary integrations.
Performance
Compared to naive RAG approaches that dump entire documents into context windows, DevRev's knowledge graph delivers only the precise context needed - reducing token consumption by orders of magnitude while maintaining answer quality.
One foundation. All surfaces - apps, search, workflows, agents, and marketplace - operate on a single Knowledge Graph. Permission-aware retrieval, temporal snapshots, and pre-aggregated summarization jobs deliver millisecond performance across every interaction.