# Elicit vs Iris.ai

Elicit records 1,751,507 monthly visits with +3.1% month-over-month growth and Freemium pricing. Iris.ai records 22,006 monthly visits with -27.9% growth and Contact for Pricing pricing.

| Metric | [Elicit](https://openaitools.app/tool/elicit) | [Iris.ai](https://openaitools.app/tool/iris-ai) |
| :--- | :--- | :--- |
| Website URL | https://elicit.com | https://iris.ai |
| Categories | AI Research Tool, AI Assistant, AI Summarizer | AI Knowledge Management, AI Research Tool, AI Summarizer, AI Chatbot |
| Pricing Model | Freemium | Contact for Pricing |
| Monthly Visits | 1,751,507 | 22,006 |
| MoM Growth Rate | +3.1% | -27.9% |
| Primary Market | United States | India |
| Direct Visits | 849,665 | 8,758 |
| Review Score | 4.6 | 4.3 |
| Saved Count | 24 | 4 |
| Supported Platforms | Website | Website |

## Elicit

Elicit is an AI research assistant built for scientific and evidence-heavy work. Instead of returning a single chat answer, it searches academic literature and clinical trial registries, then produces structured artifacts — reports, comparison tables, figures, calculations and slides — where each claim carries sentence-level citations to the underlying source.

The product spans several workflows. A research agent handles high-stakes questions by gathering evidence across scientific databases, public data sources and internally uploaded documents. Semantic search makes it possible to find relevant papers without knowing the exact keywords, and research reports follow a process inspired by systematic reviews, with the ability to change which papers and data points are included. For systematic literature reviews, Elicit automates screening and data extraction, with users reporting up to 80% time savings.

Additional features support longer research programs: a Library stores and organizes sources for reuse, Routines monitor new evidence so ongoing work stays current, and a shared research hub lets people and AI agents work from the same evidence. Teams in pharma, academia, medical devices, policy, consumer goods and industrials use Elicit, and pricing combines a free tier with paid plans.

**Pricing & Plans:** Elicit offers a free tier plus paid individual and team plans; the site references pricing tiers for individuals, professionals and organizations, so check the pricing page for current rates.

- **Research agent:** A research agent gathers evidence across scientific databases, journals, public data and your own uploads, then produces cited reports, tables, figures and slides.
- **Semantic literature search:** Semantic search across more than 138 million academic papers and 545,000 clinical trials, without needing exact keywords.
- **Customizable research reports:** High-quality research briefs inspired by systematic review methodology, with deep customization of which papers and data are included.
- **Systematic review automation:** Automated screening and data extraction for systematic reviews, with researchers reporting up to 80% time savings.
- **Library and Routines:** Store sources in a library for reuse, and set Routines so new evidence keeps your work current.

**Strengths:** Sentence-level citations make claims traceable; Handles large-scale reviews, up to 1,000 papers and 20,000 data points; Automates the tedious screening and extraction steps of systematic reviews; Combines external literature with your own uploaded documents

[Profile (Markdown)](https://openaitools.app/tool/elicit.md)

## Iris.ai

Iris.ai addresses a specific problem in enterprise AI: in fields where a wrong answer carries real cost, it is not enough for a language model to be fluent. The platform acts as a harness around the model, defining which documents and data sources it is allowed to read, and recording how each answer was assembled so results can be audited and reproduced rather than trusted on faith.

The company has been working on scientific text understanding for around a decade and applies that experience to technical literature, patents, internal reports and structured enterprise systems. The product line is organized around three entry points: Axion for converting unstructured data into AI-ready intelligence, Neuralith for building a knowledge engine over enterprise content, and RSpace for precision intelligence in complex research and development workflows.

Iris.ai sells to organizations rather than individuals, so entry is through a demo request and pricing is quoted per engagement. Documentation, help center articles, case studies and webinar resources are published on the site for evaluation before contact. It remains an actively developed commercial platform rather than a downloadable consumer app.

**Pricing & Plans:** Contact for pricing. Iris.ai sells to enterprises and R&D organizations through a demo request and tailored quotations rather than published self-serve plans; there is no listed free tier.

- **Model grounding and control:** Defines which documents and internal sources a language model may read, restricting answers to approved material.
- **Step-by-step answer tracing:** Measures and records how an answer was assembled so outputs can be audited and reproduced.
- **Scientific text understanding:** Applies a decade of NLP work on technical literature and patents to interpret dense scientific language.
- **Data-to-AI pipelines:** Turns unstructured documents and enterprise data into structured, AI-ready intelligence.
- **R&D knowledge engines:** Builds searchable knowledge layers over internal repositories for research and engineering teams.

**Strengths:** Purpose-built for high-stakes domains where wrong answers are costly; Controlled model grounding with source restrictions; Traceable, reproducible answers suited to audit and review; Roughly a decade of scientific text understanding experience

**Limitations:** No published self-serve pricing or free tier; Onboarding requires a demo request and sales process; Aimed at organizations with substantial document corpora, not individual users

[Profile (Markdown)](https://openaitools.app/tool/iris-ai.md)

## Frequently Asked Questions

### How do Elicit and Iris.ai compare in monthly traffic?

Elicit has 1,751,507 monthly visits, while Iris.ai has 22,006. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Elicit has a month-over-month growth rate of +3.1%; Iris.ai has -27.9%.

### How does pricing compare?

Elicit: Freemium. Elicit offers a free tier plus paid individual and team plans; the site references pricing tiers for individuals, professionals and organizations, so check the pricing page for current rates. Iris.ai: Contact for Pricing. Contact for pricing. Iris.ai sells to enterprises and R&D organizations through a demo request and tailored quotations rather than published self-serve plans; there is no listed free tier.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | The AI workspace where teams and agents get work done together | [.md](https://openaitools.app/tool/t.md) |
| 2 | [Perplexity](https://openaitools.app/tool/perplexity-ai) | 88,310,223 | -3.7% | Freemium | Real-time AI answer engine and research workspace combining live web citations with frontier reasoning models. | [.md](https://openaitools.app/tool/perplexity-ai.md) |
| 3 | [Kimi AI](https://openaitools.app/tool/kimi-chat) | 19,632,261 | -23.4% | Free | Moonshot AI's long-context assistant for research, coding, and agentic work | [.md](https://openaitools.app/tool/kimi-chat.md) |
| 4 | [Semantic Scholar](https://openaitools.app/tool/semantic-scholar) | 8,198,672 | +5.8% | Free | Completely free access to a massive scientific literature index, but lacks deep conversational AI synthesis features. | [.md](https://openaitools.app/tool/semantic-scholar.md) |
| 5 | [Consensus](https://openaitools.app/tool/consensus) | 6,014,388 | -1.2% | Freemium | AI academic search engine for peer-reviewed science | [.md](https://openaitools.app/tool/consensus.md) |
| 6 | [SciSpace](https://openaitools.app/tool/scispace) | 4,464,111 | +8.6% | Freemium | Better all-in-one PDF reading and analysis workspace, but less focused on automated evidence synthesis matrices. | [.md](https://openaitools.app/tool/scispace.md) |
| 7 | [Glean](https://openaitools.app/tool/glean) | 3,301,875 | +0.1% | Contact for Pricing | Enterprise AI grounded in your company's own knowledge | [.md](https://openaitools.app/tool/glean.md) |
| 8 | [Harvey](https://openaitools.app/tool/harvey-ai) | 1,832,998 | +26.1% | Contact for Pricing | Domain-specific AI for law firms, in-house legal teams, and professional services | [.md](https://openaitools.app/tool/harvey-ai.md) |
| 9 | [Rayyan](https://openaitools.app/tool/rayyan) | 1,116,437 | +7.9% | Freemium | AI-assisted systematic review software for screening, extraction, and evidence synthesis at scale | [.md](https://openaitools.app/tool/rayyan.md) |
| 10 | [Scite](https://openaitools.app/tool/scite) | 841,974 | +1.1% | Free Trial, Contact for Pricing | Offers smart citation context analysis, but lacks Elicit's specialized automated systematic review data extraction workflows. | [.md](https://openaitools.app/tool/scite.md) |

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Source: https://openaitools.app/compare/elicit-vs-iris-ai

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