chat-recall vs Frigade: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of chat-recall and Frigade — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

chat-recall

Freemium

Makes every conversation your team has had with AI coding assistants searchable, and flags secrets leaked into those chats.

Unified Conversation Search: Full-text search across the chats, plans, task lists and notes written by five supported AI coding tools, searchable the moment they arrive.
Local Secret Redaction: Passwords and API keys are stripped on your own computer before anything is uploaded; only the last few characters are ever received.
Leaked Key Reporting: Shows every key found, whether it is still live, and how many conversations it appeared in, with support for custom in-house key formats you register.
MCP Server and Recall Tools: Exposes the history to your assistants through an MCP server so they can query past work directly rather than starting cold.
Ranked Action Plan: Derives code findings and a prioritized list of what to fix next, written out as CODE_TASKS.md.
Self-Closing Bug Tasks: Each detected bug becomes a task with a sketched fix, and closes itself once the problem is actually gone.
Config Distribution: Skills and MCP configuration follow you to every machine and to whichever assistant you pick up next, with a per-machine view of what is missing.
Per-Project Rules: Mark a project as a prototype or a live product once, and every assistant that opens it plays by the matching rules.

Credential Incident Response: Find which keys were pasted into assistant conversations, whether they are still valid, and where they spread.
Recovering Past Decisions: Search months of AI conversations to recover a plan or rationale instead of asking the same question again.
Onboarding a New Machine: Sign in on a new laptop and get the full conversation history and every accumulated skill without copying files by hand.
Switching Assistants: Try a different AI coding tool without losing the add-ons and context built up in the previous one.
Team Knowledge Sharing: Share project history selectively with teammates and assign follow-up work from a shared task board.
Security Review Before Shipping: Run the secret monitor and code findings over accumulated history as a pre-release check.

Paid

AI product assistant that learns your app by using it, then answers questions, runs workflows, and guides users in-product.

Live Product Learning: Agents use the application the way a real user would and re-document workflows every release, so answers reflect the product as it is today rather than outdated help articles.
Skills and Tool Calls: The assistant can take actions inside the product and complete a step on the user's behalf, no custom code required for each workflow.
Generative UI Answers: Responses render as interactive UI elements instead of plain chat text, so the user sees the actual controls involved in a task.
AI-Generated Tours and Nudges: Product tours and in-app nudges are built on demand from the live UI with prompt-based creation, no manual element tagging, and self-healing when the UI changes.
Assist API: Teams that already run their own agent can plug it into Frigade so it inherits product expertise without a rebuild.
Engage React Components: Drop-in React components for onboarding checklists, flows, and product tours.
Friction Insights: Reporting on where users get stuck and why, with dashboards, Slack alerts, and webhooks into PostHog, Amplitude, Mixpanel, and Segment.
Enterprise Deployment Options: Cloud or self-hosted with your own LLM keys, SOC 2 Type II, GDPR compliance, SSO via SAML 2.0, and EU data residency.

Support Deflection: Answer a user's question inside the product and resolve the workflow before a support ticket is ever opened.
User Activation: Guide brand-new users through account setup and first-run configuration so they reach value faster.
Virtual CSM: Provide account-level guidance across customer tiers without staffing a human success manager on every account.
Feature Adoption: Surface newly shipped features in context, at the moment a user is doing related work.
Expansion and Upsell: Prompt in-product upgrade paths where the user already feels the limitation.
Agent Enablement: Use the Assist API to give an existing in-house support agent accurate, current knowledge of the product UI.