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Enterprise AI platform

The enterprise platform for AI agents and workflows

Connect your company data, build agents and automated workflows on it, and run them with enterprise security, cost controls, and a full audit trail.

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Integrations
80+
Model providers
9+
Uptime SLA
99.9%
Deployment options
3
Bhogar Observability - Traces & Logs page listing workflow and agent traces with success and running status, duration, and live-refresh toggle.

Works with

  • SharePoint
  • Google Drive
  • Confluence
  • Slack
  • Microsoft Teams
  • Jira
  • ServiceNow
  • Salesforce
  • GitHub
  • Azure DevOps
  • PostgreSQL
  • Snowflake
All 80+ integrations

Product

Build, run, and govern AI in one portal

Screens from the Bhogar portal. Each tile links to the capability page.

All eight capabilities

Workflows

Durable workflows with approvals built in.

Multi-step processes - onboarding, invoice review, incident triage, KYC - run as checkpointed DAGs with human approval gates.

Bhogar AI Studio - Workflows page listing 45 workflows such as HR Onboarding Sequential Flow, Finance Invoice Parallel Review, and ITOps Incident Triage with Approval.

Agents

Task agents with a defined job, versioned.

211 agents across content, HR, and finance - each with a type, status, and version, grouped into teams and chains.

Bhogar AI Studio - Agents page listing task agents such as Content SEO Optimizer, HR Policy Advisor, and Finance Fraud Screener with status and version.

Knowledge & RAG

Domain knowledge, indexed and cited.

Knowledge bases per domain with document and chunk counts, retrieval engines, knowledge graph, ontology, and taxonomy tabs.

Bhogar AI Studio - Knowledge Bases page listing 17 knowledge bases including Legal Services, Telecommunications, ROI Value Realization, and AML KYC Compliance.

Guardrails & Governance

Policy checks on every call.

Token and cost caps, PII and PHI redaction, content moderation, topic restriction, and destructive-tool blocking - with trigger counts.

Bhogar workspace Guardrails page listing active guardrails such as Token Limit, Per-Request Cost Cap, PII Protection, Content Moderation, and Healthcare PHI Redaction.

Data & Integrations

Your systems, connected with managed credentials.

Microsoft 365, Teams, Jira, GitHub, PostgreSQL, Slack, S3, and more - each credential tested and health-checked from the portal.

Bhogar Platform Services - Integrations page listing configured credentials for Microsoft 365 Outlook and Teams, Jira Cloud, GitHub, PostgreSQL, Slack, and Amazon S3 with health status.

How it works

How Bhogar works

  1. Step 1

    Connect

    Point Bhogar at documents, databases, tickets, CRM, code, and chat. Source permissions come across with the data.

  2. Step 2

    Build

    Give an agent a role, knowledge, and tools. Compose multi-step workflows with approvals where a person should decide.

  3. Step 3

    Run and measure

    Every call passes PII, content, and budget policy. Every run is traced, costed, and rolled up per team.

Solutions

Solutions by team

Each solution connects to the systems the team already uses and is measured against a metric the team already reports.

All departments By industry Use cases

Security and compliance

Retrieval respects the permissions of the person asking. Every agent action is traced with its sources. Your content is never used for model training. Deploy in Bhogar cloud, your VPC, or on-premises.

Security overviewEnterprise deployment
  • SOC 2 Type IICertified
  • ISO 27001Aligned
  • GDPRCompliant
  • CCPACompliant
  • HIPAA ReadyAvailable
  • EU-US DPFCompliant

Blog

Latest from the blog

All articles

ai · 1 min

RAG vs Fine-Tuning vs Long Context: Choosing the Right Tool

When does RAG win over fine-tuning or long-context prompting? Our 2026 decision framework with cost, freshness and accuracy trade-offs.

April 19, 2026

product · 1 min

Visual Workflow Builder vs Code: When Each Wins

Visual builders win on cycle time and visibility; code wins on flexibility. Here is how Bhogar AI lets you mix both in one workflow.

April 18, 2026

engineering · 1 min

Chunking Strategies: Fixed, Sentence, Semantic and Document-Aware

Chunking is where most RAG systems fail silently. Here are four chunking strategies, when each one wins, and how Bhogar AI auto-selects per document type.

April 18, 2026

See Bhogar on your own data

Book a 45-minute working session. We connect one of your sources, build one agent, run one governed workflow, and review the trace together.

Book a demoSee pricing