.// ARCHITECTURE
Built from the database up, not the chatbot down.
Most AI platforms bolt a language model onto existing tools. Vera starts with a structured operations layer — 920+ tables, 1,607 RLS policies, 26 modules — then adds intelligence and automation on top.
Context Engine
Ingests 920+ database tables to build a live semantic graph of your enterprise.
Semantic Layer
Maps intent to authorized plans using 1,607 RLS policies and role-based access.
Action Engine
Executes governed actions across 26 modules with full audit trails and rollbacks.
| Feature | Layer 01: Context | Layer 02: Semantic | Layer 03: Action |
|---|---|---|---|
| Primary Role | Data ingestion & linking | Intent & Permission mapping | Workflow execution |
| Data Sources | 920+ DB Tables | 1,607 RLS Policies | 26 Business Modules |
| Output | Live Entity Graph | Validated Execution Plan | Governed Actions + Audit |
| Technology | Vector + Graph DB | Reasoning Models | Governed Runtime |
.// LAYER 01 — CONTEXT ENGINE
Context Engine
Before an agent can act, it needs to understand. The Context Engine ingests data from 920+ enterprise tables and builds a live, contextual understanding of your people, processes, documents, and systems.
- 01
Entity Resolution
Deduplicates and links records across systems — matching vendor IDs, contact emails, and contract references into unified entities.
- 02
Relationship Mapping
Connects vendors to contracts, deals to contacts, tickets to products — building a semantic graph agents can traverse.
- 03
Live Synchronization
Changes in connected systems propagate in real time. Agents always reason over current data, not stale snapshots.
Context Engine Output
.// LAYER 02 — SEMANTIC LAYER
Semantic Processing
Semantic Layer
The Semantic Layer translates user intent into authorized execution plans. It parses what the user needs, checks what they are permitted to do, and constructs a multi-step plan that respects every governance boundary.
- 01
Intent Parsing
Natural language requests are decomposed into structured operations with domain-specific understanding.
- 02
Permission Enforcement
Every planned action is checked against RBAC policies and row-level security before execution begins.
- 03
Execution Planning
Complex requests become ordered, dependency-aware execution plans with rollback strategies for each step.
.// LAYER 03 — ACTION ENGINE
Action Engine
The Action Engine executes multi-step workflows across systems with full permission enforcement. Every action is logged, every decision is traceable, and every outcome feeds back into the context graph.
- 01
Workflow Orchestration
Multi-step actions execute in order, with each step validated before the next begins. Failures trigger automatic rollback.
- 02
Audit Logging
Every action, decision, and data access is recorded with timestamps, user context, and reasoning chains.
- 03
Cross-System Execution
Agents write to CRMs, update financial systems, create tickets, send notifications — all through governed connectors.
Execution Pipeline
.// DEPLOYMENT
Deploy where your data lives.
Cloud-hosted by default. Self-hosted models for full data control. Enterprise hybrid for regulated industries. Your data never leaves the boundaries you define.
Data Sources
920+ Tables
CRM, Finance, HR, Support, Ops
Vera Platform
AI + Agents + OS
Context → Reasoning → Action
Outputs
Governed Actions
Audit trails, reports, updates
Cloud Hosted
Fully managed by Vera. Zero infrastructure to maintain. Default for Pro and Team tiers.
Available NowSelf-Hosted Models
Run Qwen 3.5-9B on your own GPU infrastructure. Zero vendor lock-in. Full data control.
Available NowEnterprise Hybrid
Org-isolated compute, data residency controls, and environment management. Custom deployment.
Enterprise Tier.// INTEGRATIONS
Connected to the systems you already use.
Vera connects to your CRM, financial systems, support platforms, HR tools, and communication channels through native integrations and MCP-compatible connectors.
| Category | Integrations | Protocol | Status |
|---|---|---|---|
| CRM | Salesforce, HubSpot, Pipedrive | REST + MCP | Live |
| Finance | QuickBooks, Xero, Stripe, NetSuite | REST + MCP | Live |
| Support | Zendesk, Intercom, Freshdesk | REST + Webhooks | Live |
| HR | BambooHR, Workday, Gusto | REST + MCP | Live |
| Communication | Slack, Microsoft Teams, Email (SMTP/IMAP) | WebSocket + REST | Live |
| Storage | Google Drive, SharePoint, Notion, Confluence | REST + MCP | Live |
| Development | GitHub, GitLab, Jira, Linear | REST + Webhooks | Live |
| Data | Snowflake, BigQuery, PostgreSQL, Redshift | SQL + MCP | Beta |
Enterprise scale. Enterprise governance.
The only AI agent platform built from the database up — not bolted onto a chatbot.
.// READY TO DEPLOY?
Your competitors deployed AI agents last quarter. What's your timeline?
See how Vera puts AI agents into production across Finance, Sales, Support, HR, and Compliance — with governance your enterprise requires. Start with a 30-minute discovery call.
See how it works
Context Engine, Semantic Layer, and Action Engine — see the three-layer architecture that powers governed agent execution.
Explore the platform →From pilot to production in 4 weeks
In 30 minutes, describe your most painful workflow. Within 48 hours, receive a custom POC plan with ROI projections, integration requirements, and a deployment roadmap.
Book a discovery call →