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Ocular

Ocular is an organization-focused search and chat application that uses company data to support conventional search and conversational queries. Its repository describes a modular generative-AI search platform with app connectors, configurable infrastructure, and governance features.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Ocular — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Ocular when the goal is to combine search and AI chat over organizational data, and when the team can configure a backend LLM provider and, where needed, app-specific credentials.

Who it is for

  • Organizations seeking search and conversational access to internal knowledge.
  • Teams evaluating a self-hosted generative-AI search application.

Documented uses

  • Search organizational data through a Google-like interface.
  • Ask conversational questions about company information.
  • Connect app data sources for document indexing using app-specific API keys.
  • Adapt the search platform to custom connectors, language models, or vector databases.
Before you choose

Requirements & limits

The README documents a Docker-based local setup and a managed cloud or self-hosted enterprise offering inquiry. It identifies the repository license as Elastic License 2.0.

  • Local setup requires Docker and a configured LLM provider; OpenAI is the default named provider.
  • Document indexing from connected apps requires API keys for those apps.
  • The repository lists role-based access control and audit logs among its governance features.
  • The repository is TypeScript and states that it is licensed under Elastic License 2.0.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up Ocular locally with Docker

Prepare a local Ocular instance and open its account-creation page.

Before you start

  • Docker installed and running
  • An OpenAI key for the default LLM provider

Steps

  1. Clone the Ocular repository and change into its directory.

  2. Add the required OpenAI environment variables to env.local in the project home directory.

  3. Start the local containers with the command below.

    Documented command
    docker compose -f docker-compose.local.yml up --build --force-recreate

  4. When the Docker process completes, open http://localhost:3001/create-account.

Expected outcome

The README describes a local instance available at the account-creation page while Docker remains running.

Guide limitations

  • A backend LLM provider must be configured; OpenAI is the default.
  • Indexing documents from an app requires that app’s API keys in env.local.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Vector search

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
OcularSearch organizational data through a Google-like interface.Self-hosted, WebThe README documents a Docker-based local setup and a managed cloud or self-hosted enterprise offering inquiry. It identifies the repository license as Elastic License 2.0.
Chatbot with PDF for Semantic SearchPrepare document content as embeddings and save it to a supported vector database.WebThe repository is identified as open source and publicly visible on GitHub.
AI LLM PlaygroundAsk questions about PDF documents through an assistant interface.Web
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
OcularEngineering/ocular · Official homepage title · retained in its source language
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