Agentic Fabriq vs Traceforce: Which is Better in 2026?
A comprehensive comparison of Agentic Fabriq and Traceforce covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Agentic Fabriq if:
- →You want more affordable paid plans (from $50/mo)
- →You need agent identity management distinct from service accounts and raw tokens or scope-based permissions controlling access per agent and per user
Choose Traceforce if:
- →You need on-device agent that sees desktop and cli ai tools, not just browser traffic or risk assessment across 900+ ai applications and mcp servers
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Agentic Fabriq vs Traceforce: At a Glance
Pricing Comparison: Agentic Fabriq vs Traceforce
Understanding the pricing differences between Agentic Fabriq and Traceforce is crucial for making the right choice. Here's how their plans compare side by side.
Agentic Fabriq Pricing
Traceforce Pricing
💡 Pricing takeaway: Both Agentic Fabriq and Traceforce offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Agentic Fabriq and Traceforce stacks up.
What Makes Each Tool Unique
🔵 Unique to Agentic Fabriq
Features available in Agentic Fabriq but not in Traceforce:
- ✓Agent identity management distinct from service accounts and raw tokens
- ✓Scope-based permissions controlling access per agent and per user
- ✓Secure credential and token vault
- ✓Real-time audit logging of every invocation, issuance, and block
- ✓MCP tool integrations, including deploying your own MCP server
- ✓SSO via Okta, SAML, or OIDC on paid tiers
🟣 Unique to Traceforce
Features available in Traceforce but not in Agentic Fabriq:
- ✓On-device agent that sees desktop and CLI AI tools, not just browser traffic
- ✓Risk assessment across 900+ AI applications and MCP servers
- ✓Sensitive-data leakage detection in Claude, ChatGPT, and Copilot
- ✓Dangerous-action detection for Claude Code, Cursor, and Codex
- ✓MCP registry with a security approval workflow
- ✓Full telemetry API access plus an open-source MCP scanner
Use Case Recommendations
Best for: Agentic Fabriq
Agentic Fabriq is identity and permissioning infrastructure for AI agents. The problem it names is that existing identity systems were built for humans and services, not autonomous non-human actors that access internal tools and company data, execute workflows across systems, act on behalf of specific users, and talk to other agents. In practice that leaves teams in three bad positions: engineers rebuilding custom auth logic for every agent, no standard way to represent an agent's identity so agents get flattened into service accounts and raw tokens, and security teams with no monitoring or audit trail over what agents actually did. Fabriq is the hub that fixes all three. It issues and manages agent identities, applies scope-based permissions so you control precisely what each agent can access and do for each user, and holds credentials and tokens in a secure vault rather than in environment variables scattered across services. Every action is logged for real-time audit — the live view shows calls being invoked, tokens issued, and dangerous operations blocked as they happen. There is SDK and API access plus MCP tool integrations, with the ability to deploy your own MCP server and register custom tools on paid tiers. The company reports 500+ agents regulated through the platform and is exhibiting at Black Hat USA 2026.
Ideal use cases:
- •Teams or individuals who need agent identity management distinct from service accounts and raw tokens
- •Teams or individuals who need scope-based permissions controlling access per agent and per user
- •Teams or individuals who need secure credential and token vault
- •Teams or individuals who need real-time audit logging of every invocation, issuance, and block
- •Anyone focused on agent identity workflows
- •Anyone focused on permissions workflows
Best for: Traceforce
Traceforce is an AI security and control platform that operates at the device layer rather than on the network. The observation behind it is that AI usage has moved out of the browser — Claude, ChatGPT desktop, Copilot, Cursor, and Codex all run as native applications or CLI tools, and a security stack that inspects browser traffic simply cannot see what they do. Traceforce runs an agent on the device, which is where it can watch actions as they happen and control them. Capabilities include risk assessment across 900+ AI apps and MCP servers, sensitive-data leakage detection in Claude, ChatGPT, and Copilot, and detection of dangerous actions taken by coding agents including Claude Code, Cursor, and Codex — the category of thing where an agent decides to delete a directory or push a secret and nobody finds out until later. All telemetry is reachable through an API rather than being locked in a dashboard. The paid tier adds runtime control over Claude Cowork and ChatGPT desktop, admin controls for connectors, and an MCP registry with a security approval process, which is the piece that turns shadow-MCP sprawl into something reviewable. The company also publishes an open-source MCP scanner. Pricing is per device, and the free trial covers 10 devices for 30 days with no card.
Ideal use cases:
- •Teams or individuals who need on-device agent that sees desktop and cli ai tools, not just browser traffic
- •Teams or individuals who need risk assessment across 900+ ai applications and mcp servers
- •Teams or individuals who need sensitive-data leakage detection in claude, chatgpt, and copilot
- •Teams or individuals who need dangerous-action detection for claude code, cursor, and codex
- •Anyone focused on ai security workflows
- •Anyone focused on dlp workflows
🤖 Other AI Agent Infrastructure Tools to Consider
Agentic Fabriq and Traceforce aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
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Frequently Asked Questions
Is Agentic Fabriq better than Traceforce?
It depends on your needs. Agentic Fabriq offers 6 key features including Agent identity management distinct from service accounts and raw tokens and Scope-based permissions controlling access per agent and per user, while Traceforce provides 6 features including On-device agent that sees desktop and CLI AI tools, not just browser traffic and Risk assessment across 900+ AI applications and MCP servers. Agentic Fabriq uses a freemium model with a free tier, while Traceforce is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is Agentic Fabriq cheaper than Traceforce?
Traceforce doesn't have standard paid plans, while Agentic Fabriq starts at $50/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Agentic Fabriq and Traceforce together?
Yes, many users combine Agentic Fabriq and Traceforce in their workflow. Agentic Fabriq excels at agent identity management distinct from service accounts and raw tokens, while Traceforce shines with on-device agent that sees desktop and cli ai tools, not just browser traffic. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Agentic Fabriq and Traceforce?
While both are ai agent infrastructure tools, Agentic Fabriq emphasizes agent identity management distinct from service accounts and raw tokens, whereas Traceforce is known for on-device agent that sees desktop and cli ai tools, not just browser traffic. The best choice depends on your specific workflow and feature priorities.
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