Go beyond search with Agentic Retrieval

Ragie’s next-generation retrieval engine handles multi-step queries, self-checks results, and delivers grounded answers with citations. Built for real-world agents and applications.

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Standard RAG retrieves. Agentic Retrieval reasons.

Traditional RAG often struggles with noisy queries, imperfect data, or answers that sound right but aren’t. Agentic Retrieval breaks questions into parts, searches across multiple sources, evaluates candidate results, and assembles clear, cited answers you can trust.

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Query decomposition
Breaks down complex, multi-step questions into smaller, manageable tasks that can be addressed individually.
Evidence gathering
Pulls from multiple sources using complementary search strategies to build a complete picture.
Reflect & evaluate
Validates findings, rejects false positives, and re-queries when needed to improve accuracy.
Answer assembly
Synthesizes context into a clear, coherent, and trustworthy response.
Citation
Every response links back to your underlying data for transparency and verification.

Ask your toughest questions.

Agentic Retrieval is designed for real-world complexity. Whether it’s tracing financial performance, analyzing contracts, or synthesizing clinical data, Ragie connects the dots across documents, tools, and time so you always get one clear, accurate answer.

Finance
LEGAL
MEDICAL
Customer support

Decode the numbers

Agentic Retrieval goes beyond surface-level lookups to connect financial data across years, reconcile reports, and benchmark performance against competitors. It can trace shifts in margins, costs, or revenue streams, and explain the “why” behind complex trends hidden across multiple filings.

How did gross margin trends shift from FY2021 to FY2023, and how do they compare to industry competitors?

Searched, planned, coded, and cited answer.

Gross margin improved from 4.2% in FY2021 to 6.1% in FY2023, largely due to cost reductions and international growth. Compared to competitors, the company’s margins remain 1.5% below the industry median, highlighting ongoing pricing pressure.

Annual_Financial_Report_2023.pdf

Enterprise ready

Ragie is built for enterprise-scale workloads with multi-tenant architecture, SOC 2-compliant security, and seamless performance at any scale.

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VPC
Ingests data from various sources like text, PDFs, and images via APIs and direct connectors, ensuring seamless integration and updates.
SOC2 (coming soon)
Isolates key information from different formats, filtering out irrelevant data.
Single tenant deployment
Uses techniques like table chunking to break data into meaningful segments while preserving context.

Navigate the fine print

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Legal documents are long, interconnected, and often contradictory. Agentic Retrieval can parse case law, contracts, and regulatory filings across time, resolving references and surfacing the precedent or clause that matters. It delivers grounded answers to questions that span multiple statutes or rulings.

Which precedents are most relevant to the company’s new data privacy policy, and do they align with EU directives?

Searched, planned, coded, and cited answer.

The 2023 update references Case A v. DataCorp (2021) and Smith v. Secure Systems (2022). Both rulings align with GDPR requirements for user consent and data portability, ensuring the policy is consistent with EU directives.

EU_Privacy_Directives_2022.txt

Unlock critical insights

Medical knowledge is scattered across research papers, trial results, and clinical guidelines. Agentic Retrieval synthesizes insights across these sources, compares treatment outcomes, and highlights evolving standards of care. And with Ragie’s HIPAA compliance, you can do it securely while protecting sensitive patient data.

What evidence supports the effectiveness of the new treatment protocol across multiple trials, and how does it compare to existing standards of care?

Searched, planned, coded, and cited answer.

Trials from 2021–2023 show the protocol improved recovery rates by 18% and reduced complications by 12%. Compared to standard care, patients reported higher mobility scores and faster recovery times in 3 out of 4 studies.

Clinical_Trial_Summary_2023.pdf

Resolve issues faster

Support issues rarely exist in isolation. Agentic Retrieval can connect tickets, product logs, and knowledge base articles to explain recurring problems, identify systemic causes, and suggest the most effective resolutions. It helps surface insights that no single ticket could show on its own.

What are the top drivers of customer churn based on last year’s support tickets, and how do they differ from prior years?

Searched, planned, coded, and cited answer.

In 2024, the leading causes were unresolved billing disputes and repeated login failures. Compared to 2023, billing escalations increased by 22%, while login issues dropped by 14%. This suggests retention risk has shifted to financial disputes.

Support_Tickets_Q2_2025.csv

Use Agentic Retrieval instantly with Base Chat

Base Chat is the fastest way to chat with your company’s knowledge base, powered by Ragie. With Agentic Retrieval built in, Deep Search mode gets you clear, accurate answers to even the hardest questions.

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The world’s first Context-Aware MCP Server for Agents

Agentic Retrieval depends on agents accessing the right data. Ragie’s MCP Server makes it seamless. With a single API key, connect agents or custom apps directly to your knowledge base.

Context-Aware descriptions help agents understand your data, discover the right information, and route tools with accuracy and consistency.
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Ragie is Agent Ready.

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