Cassidy AI vs Langbase

Detailed side-by-side comparison to help you choose the right tool

Cassidy AI

🟢No Code

AI Tools for Business

Cassidy builds knowledge-grounded AI agents and workflows for operationally complex industries — insurance, manufacturing, employee benefits — inside Teams, Slack, Chrome, and Word.

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Starting Price

Free
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Langbase

🔴Developer

AI developer platform

A serverless platform for building, deploying, and operating AI agents and retrieval workflows.

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Starting Price

Free
Full ReviewVisit Site

Feature Comparison

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FeatureCassidy AILangbase
CategoryAI Tools for BusinessAI developer platform
Pricing Plans200 tiers272 tiers
Starting PriceFreeFree
Key Features
  • • Core workflow: Cassidy builds agents and workflows for CRM context, meetings, RFP responses, support triage, and technical knowledge retrieval.
  • • Integrations and scale: The pricing page lists agents, workflows, brand voice, knowledge collections, scheduled triggers, human-in-the-loop steps, webhooks/API, conditional logic, retries, bulk execution, research blocks, audit trails, and deployments into Slack, Teams, Gmail, Outlook, Word, Excel, Chrome, and APIs.
  • • Governance and limits: Security claims include SOC 2 Type II, encryption, no model training on customer data, SSO on higher tiers, and GDPR support.

    Cassidy AI - Pros & Cons

    Pros

    • ✓Vertical playbooks for insurance, PEO, industrials, and professional services beat generic agent templates
    • ✓Model-agnostic runtime — no lock-in on any single LLM provider
    • ✓Free Starter with 3 seats, 10K credits/month, and 30K pages is a genuine evaluation tier, not a teaser

    Cons

    • ✗Business pricing is custom only — no published rate card makes budgeting and CFO conversations harder
    • ✗Connector library is narrower than horizontal-first competitors like Dust or Glean
    • ✗Advanced features (audit trail, custom triggers, bulk execution) require Business — Starter is essentially a trial

    Langbase - Pros & Cons

    Pros

    • ✓Serverless APIs reduce initial runtime and deployment work
    • ✓Managed memory and retrieval cover common assistant requirements
    • ✓MCP server support can expose platform capabilities to compatible clients

    Cons

    • ✗Platform abstraction can make low-level debugging and portability harder
    • ✗Cost depends on request volume, storage, and underlying model usage
    • ✗Current quotas and commercial terms require manual verification

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    🔒 Security & Compliance Comparison

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    Security FeatureCassidy AILangbase
    SOC2✅ Yes—
    GDPR✅ Yes—
    HIPAA✅ Yes—
    SSO✅ Yes—
    Self-Hosted❌ No—
    On-Prem❌ No—
    RBAC✅ Yes—
    Audit Log✅ Yes—
    Open Source❌ No—
    API Key Auth✅ Yes—
    Encryption at Rest✅ Yes—
    Encryption in Transit✅ Yes—
    Data Residency——
    Data Retentionconfigurable—
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