CrewAI vs Sinequa (2026): Pricing, Features & Verdict

Why choose CrewAI

• Has a free plan (Sinequa does not)
• Higher Cost score (7/10 vs 3/10)
• Higher Analytics score (7/10 vs 6/10)
• Better fit for small business (4/10 vs 1/10)

Why choose Sinequa

• Higher Scalability score (9/10 vs 6/10)
• Higher Security score (9/10 vs 7/10)

CrewAI

Pros

• The core framework is MIT-licensed and free to self-host, so teams can prototype multi-agent systems without licensing costs.
• The role-based Crews model and the event-driven Flows model give developers a clear structure, with sequential and hierarchical task processes.
• It works with most LLMs through LiteLLM or native providers, and it supports MCP servers, A2A, and more than 40 built-in tools.
• AMP includes OAuth-based connectors for Salesforce, HubSpot, Slack, and Gmail, plus REST API and webhook triggers.
• Enterprise buyers can deploy in their own VPC or on their own infrastructure, with SSO, RBAC, and PII redaction.

Cons

• No public price exists between the free 50-execution Basic tier and a custom Enterprise quote.
• Reviewers report heavy token use, because every agent step is an LLM call and multi-agent crews add to the cost.
• Python knowledge is effectively required, and reviewers describe the learning curve as steep for newcomers.
• Independent reviews say long-running pause and resume, horizontal scaling, and error recovery need custom work.
• Smaller open-source models, around 7B parameters, reportedly struggle with CrewAI's function calling.
• Compliance claims (SOC 2 type, HIPAA) vary between third-party sources and should be confirmed directly with the vendor.

Sinequa

Pros

• The connector library covers more than 200 enterprise systems, including SharePoint, SAP, ServiceNow, Salesforce, Confluence and the Teamcenter PLM system.
• Retrieval respects each source system's access rights at query time, so assistants and agents only surface content the user is cleared to see.
• Deployment options are unusually broad: on-premises, private or air-gapped cloud, native Azure, or managed SaaS.
• Assistants are LLM-agnostic, and the MCP server exposes Sinequa search to Claude, ChatGPT, Copilot and Gemini clients.
• Analysts recognize it: a Leader in the QKS SPARK Matrix for Enterprise AI Search (Q4 2025), and Gartner Peer Insights averages about 4.3 from roughly 60 reviews.

Cons

• There is no public pricing, and third-party sources report minimum terms of about three years with auto-renewal and a three-month cancellation notice.
• Reviewers describe implementation as a business change program, and deeper configuration often needs vendor assistance.
• Some Gartner reviewers report indexing delays that hurt retrieval of freshly updated content.
• Setting up and governing the generative AI features adds complexity, according to critical reviews.
• Product documentation sits behind a ChapsVision login, and the ongoing rebranding into Argonos can confuse buyers.