BrainDog vs RELAI
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
BrainDog compared with RELAI
| Detail |
BrainDog |
RELAI |
| What it does | A workspace for projects, decisions and money that every agent reads and updates
| The continual learning engine for AI agents
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Free
| Freemium
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| Pricing | Not given
| RELAI Free: $0. RELAI Enterprise: Custom pricing.
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| Key features | - Connect coding agents via MCP protocol (Claude Code, Cursor and others)
- Centralized project tracking with decisions and money
- Audit trail with every change signed and undoable
- Approval controls for money, deletions and key access
- Learning system that reduces approval requests after 10 similar actions
- Team collaboration with email invitations and role-based access
- Built-in Slash assistant with 20 questions per month on free plan
- 1,000 automation runs per month on free plan
- Full data export available anytime
- Sealed backups every night with secure key storage
| - Capture signals from code, requirements, and production traces
- Build and maintain EvalsWiki as versioned behavioral knowledge
- Find missing eval coverage and unclear expectations
- Generate complete evals with scenarios, environments, and evaluators
- Optimize harness across prompts, tools, workflows, and code
- Multi-objective optimization for quality, cost, latency, and KPIs
- Model selection, migration, and routing with evaluation
- Regression-controlled improvement with evaluation evidence
- Versioned storage in repository with pull requests
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| What makes it different | - Works with any agent that speaks MCP protocol, not vendor-locked to one tool
- Integrates work tracking and financial management in one place agents automatically read
- Full audit trail and undo capability for every change
- Learns from agent behavior to reduce approval overhead over time
- Free tier includes all features with no credit card required
| - Turns failures into replayable learning environments
- Prevents regressions by keeping previous evals in the loop
- Integrates with existing observability stacks and traces
- Preserves business intelligence versioned in repository
- Adapts harness to model changes without redefining use cases
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | 12 ▲ +12 (up) since last check | 23 ● no change since last check |
| Trust Flow (Majestic) | 0 | 13 |
| Citation Flow (Majestic) | 0 | 25 |
| Referring domains (Majestic) | 0 | 79 |
4 details filled in for both companies.
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