| What it does | AI automation company delivering measurable ROI without enterprise prices
| The continual learning engine for AI agents
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| Stage | Startup
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| Founded | 2025
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| Based in | US
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| Pricing model | Paid
| Freemium
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| Pricing | Pilots: $5,000–$15,000 fixed-price per workflow. Retainers: from $1,500/month for up to 15 people, $2,500–$3,000/month for 15–50 people, from $7,000/month for 50–100 people, custom pricing for 100+ people. All retainers include maintenance, model upgrades, new automations each sprint, and support at
| RELAI Free: $0. RELAI Enterprise: Custom pricing.
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| Key features | - AI Agent Development with OpenAI, Anthropic, and LangGraph
- Workflow Automation connecting CRM, billing, reporting and ops stack
- Fixed-price pilots with ROI verification and documentation
- Voice AI Development for automated phone agents
- Healthcare AI with HIPAA compliance and self-hosted deployment
- AI App Development with RAG and multi-model routing
- On-premises and air-gap deployment options
- Direct access to founder and engineering team with priority response under 4 hours
- Free 30-minute consultation with no obligation or sales pitch
| - 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 | - Measurable ROI-first approach: every engagement defined by business outcomes, not hours delivered
- No lock-in with month-to-month retainers and IP that transfers on day one
- Founder-led technical scoping ensures the quoted architecture is the architecture delivered
- All maintenance, model upgrades, and fixes included in one flat monthly retainer
- Fraction of the cost of hiring an in-house AI team while delivering results from week one
| - 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) | 25 ▲ +1 (up) since last check | 23 ● no change since last check |
| Trust Flow (Majestic) | 3 | 13 |
| Citation Flow (Majestic) | 28 | 25 |
| Referring domains (Majestic) | 105 | 79 |