Deploy Accurate, Secure, and Governed Gen AI in semantic search

Our platform delivers superior relevance and faster retrieval for enterprise search, all within a secure, governed framework your organization can finally trust.

The Power of Gen AI:

For Enterprise Search

Lyzr enhances search by understanding user intent, using advanced embeddings and RAG for grounded answers, all managed with strict enterprise governance.

01

Intent Analysis

02

RAG Context

03

Answer Grounding

04

Full Governance

Powering Enterprise Workflows with

AI

From customer support to internal RAG knowledge hubs, our enterprise search solution delivers accurate answers where teams need them most.

Customer Support

Increase ticket deflection with instant, accurate answers from your knowledge base.

Internal Knowledge

Accelerate product discovery across technical specs and policies with fewer missed results.

Product Discovery

Accelerate product discovery across technical specs and policies with fewer missed results.

Stop wasting time on irrelevant results. Give your teams the trusted, precise answers they need to succeed.

Benefits of Gen AI in

Semantic Search

Increase match quality and eliminate the frustrating 'no results found' search experiences.

Accelerate time-to-answer for all users, reducing wasted time from context switching.

Deliver trusted, grounded answers with verifiable citations from your approved documents.

Built with RBAC, full encryption, audit logs, and enterprise compliance support.

Enterprise Search

Capabilities

Our end-to-end platform covers the full lifecycle: ingest, index, retrieve, RAG generation, and continuous evaluation.

Vector Embeddings

Create powerful embeddings with hybrid search and rerankers for ultimate relevance.

True RAG Orchestration

Orchestrate grounded answers with source citations and fine-grained prompt controls.

Data Source Connectors

Securely connect to Google Drive, Confluence, SharePoint, S3, and many other sources.

Granular Access Control

Enforce RBAC and ABAC policies with complete tenant isolation and sensitive PII controls.

Quality Monitoring

Track relevance metrics with user feedback loops and automated drift monitoring tools.

How Lyzr's AI Search

Compares to Others

Lyzr provides a "Bank-in-a-Box" AI framework, ensuring your generative AI banking security matches your most stringent internal standards through total isolation.

Feature

Legacy Search Tools

Generic AI Tools

Lyzr

Hybrid Search Method

Keyword Only

Vector search only

Native Hybrid Search

RAG Citations

Not Available

Basic RAG, no cites

Built-in with sources

Permissions-aware

Separate system

Limited integration

Native permission mapping

Hallucination

Not applicable

High risk, manual

Grounding and Guardrails

Eval & Analytics

Manual analysis

No built-in tools

Automated Quality Metrics

Time-to-Deploy

Lengthy setup

Requires coding

Fast, low-code deployment

No options

No options

Model-dependent

Choose your own model

Tenant Isolation

Shared resources

Varies by vendor

Dedicated tenant isolation

Why Lyzr is Built

for Enterprise

Secure By Design

Full RBAC, audit logs, and data isolation for enterprise compliance needs.

Model Flexibility

Choose your preferred LLM, embedding models, and custom deployment options.

Grounded Answers

Ensure all AI-generated answers are grounded in your trusted, private data sources.

Control

Manage performance with evals, monitoring, cost controls, and powerful admin tools.

Built Specifically for

Financial Institutions

Join a growing ecosystem of consulting and technology partners

Lyzr has completely transformed our knowledge base search. Our support team finds accurate answers 70% faster, and the RAG citations give us confidence that every result is grounded in fact. We've seen a measurable increase in ticket deflection and user trust.

KM Lead

Head of Knowledge Management

Zero

Data Exfiltration Incidents

Deploy Gen AI Search Safely

in 4 Steps

Define Scope

Define your core use case, identify data sources, and set access policies.

Connect and Index

Connect repositories, chunk your documents, and build your vector embeddings.

Configure RAG

Configure your retrieval pipeline, prompts, citations, and business safety rules.

Evaluate and Go-Live

Run evaluations on quality, monitor for drift, iterate, and launch to users.

Frequently asked questions

It combines large language models with vector search to understand query intent, not just keywords. This allows it to find conceptually related information, resulting in more relevant and accurate search results across your enterprise data, improving knowledge discovery.
By understanding the semantic meaning behind a search query, it moves beyond simple keyword matching. It finds documents that are contextually and conceptually similar, which significantly boosts the relevance of search results and minimizes incorrect or zero-result queries.
Secure deployment involves tenant isolation, robust access controls (RBAC/ABAC), data encryption, and comprehensive audit trails. Lyzr's platform is architected for enterprise security, ensuring that your sensitive data remains private and that search results respect all user permissions.
Retrieval-Augmented Generation (RAG) grounds the AI's answers in your verified company data. It first retrieves relevant documents and then uses that information to generate a response, providing citations. This dramatically reduces hallucinations and builds user trust in the AI.
Track relevance metrics with user feedback loops and automated drift monitoring tools.
Lyzr is designed for flexibility. We integrate with a wide range of popular vector databases, including Pinecone, Weaviate, Milvus, and more. You can choose the best option for your existing infrastructure or use our managed solution for a streamlined deployment.
Permissions are enforced at the point of data ingestion and retrieval. Our system syncs with your source-of-truth identity providers (like Active Directory) to ensure that users can only see search results for documents and data they are explicitly authorized to access.
We use a suite of evaluation metrics, including NDCG and hit rate, to score relevance. The platform also includes tools for user feedback loops and continuous monitoring, allowing you to track performance over time and make data-driven improvements to the search experience.
We minimize hallucinations primarily through Retrieval-Augmented Generation (RAG), which grounds all answers in your data. Additionally, we implement configurable guardrails, safety filters, and prompt controls to ensure that all generated outputs are safe, accurate, and aligned with your policies.
Our platform supports a vast ecosystem of connectors for sources like Confluence, SharePoint, Google Drive, S3, and more. We handle various unstructured data types, including PDFs, DOCX, and web pages, ensuring all your key enterprise knowledge is fully searchable.
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