Hyperresearch vs RELAI
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Hyperresearch compared with RELAI
| Detail | 
Hyperresearch | 
RELAI |
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| What it does | AI deep research API that checks every cited claim against its source
| The continual learning engine for AI agents
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| Stage | Startup
| Not given
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| Founded | 2026
| Not given
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| Based in | US
| Not given
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| Pricing model | Paid
| Freemium
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| Pricing | Not given
| RELAI Free: $0. RELAI Enterprise: Custom pricing.
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| Key features | - Searches 45+ structured sources including SEC filings, statistics agencies, scholarly indexes, books and government records
- Workspace vault with searchable full-text source storage and independence clustering
- Integrated MCP server for Claude, Cursor, ChatGPT and other clients
- Contradiction mapping identifies and investigates disagreements in evidence
- Automatic report generation with verified citations before shipping
- Citation verification API for external documents
- Markdown import and export for vault documents
- Integrated Answers MCP with ask and search tools for AI agents
| - 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 | - Every cited claim is verified against the original source before report delivery
- Searches structured sources like SEC filings and scholarly databases alongside the open web in one call
- Delivers answers with word-for-word quotes so readers can verify in one click
- Open-source CLI that powers the hosted service, maintaining feature parity
- Pay-as-you-go pricing with no minimum commitment or sales team 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
| 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
| Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 32 ▲ +4 (up) since last check | 23 ● no change since last check |
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| Trust Flow (Majestic) | 13 | 13 |
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| Citation Flow (Majestic) | 31 | 25 |
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| Referring domains (Majestic) | 71 | 79 |
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4 details filled in for both companies.
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