OramaSearch Inc.
Orama builds open-source and managed search infrastructure: full-text, vector, hybrid search, answer engines and RAG that run in browsers, servers, edge networks or customer-controlled infrastructure. Its broader current positioning is helping companies design, train and ship AI grounded in their own data and measurable outcomes.
At a Glance
- Developers and open-source teams
- Documentation and developer-tool publishers
- Ecommerce and product-catalog businesses
- Companies building AI applications, copilots and support agents
- +2 more
AI Tools by OramaSearch Inc.
(1)Orama
Open Source JavaScript Search Engine
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Latest News
OramaJS 3.2.0 released with Vietnamese support, experimental Korean tokenizer, Astro 5 migration and bundler fixes.
OramaJS v3.1.18 released.
OramaJS v3.1.16 added document pinning capability.
OramaJS v3.1.13 added seqproto serialization for disk persistence and updated the documentation URL.
Products & Services
Free, open-source, zero-dependency TypeScript search library for full-text, vector and hybrid search in browsers, servers and edge runtimes. Distributed as @orama/orama via npm and usable from browser modules and Deno/CDN imports.
Fully managed Orama service for running search and RAG at scale. It provides a simple API and web interface, projects and segregated data sources, configurable languages and embedding models, and managed full-text, vector, answer-engine and RAG capabilities.
Open-source Rust AI runtime for answer engines, copilots and search, combining a full-text search engine, vector database, LLM interface with action planning/reasoning, embeddings, RAG, JavaScript agents and Docker deployment.
The enterprise surface of the Metis Intelligence OS: connects existing data, scores what the data can support, builds verified pipelines, trains models, serves results and deploys in a customer's cloud, on-premises or dedicated infrastructure.
Market Position
Orama positions OramaJS as a lightweight, zero-dependency, embeddable alternative to hosted search and vector databases, combining full-text, vector and hybrid retrieval in one library that runs locally in browser/server/edge environments. Its broader OramaCore/Cloud offering competes with search and vector infrastructure such as Algolia, Pinecone and Weaviate, while differentiating through built-in embeddings, LLM/RAG capabilities, a JavaScript runtime and customer-controlled deployment.
Leadership
Founders
Michele Riva
Co-founder and CTO; previously a Senior Software Architect at NearForm and worked at Paramount. He created the TypeScript search engine Lyra while preparing a talk on algorithms and data structures, and presented it at WeAreDevelopers and NodeConf.
Issac J. Roth
Co-founder and CEO; previously founder and CEO of StrongLoop and CTO at Cloud-related technology companies. Crunchbase lists him as Orama's co-founder and CEO.
Angela Angelini
Early co-founder and Head of Design; has a professional background in UI/UX design.
Executive Team
Issac J. Roth
Co-founder and CEO
Founder and CEO of StrongLoop before Orama; Crunchbase identifies him as Orama's co-founder and CEO.
Michele Riva
Co-founder and CTO
Former NearForm Senior Software Architect and Paramount employee; creator of Lyra, the predecessor to Orama.
Founding Story
Orama grew out of Lyra, a small zero-dependency full-text search engine Michele Riva created in TypeScript in 2022 while at NearForm. After Paolo Insogna helped make Lyra compatible with major edge networks and the open-source project gained significant adoption, Riva and co-founders created OramaSearch Inc. in February 2023, renamed Lyra to Orama, and dedicated a full-time team to developer experience, performance and new search capabilities.
Business Model
Revenue Model
The core OramaJS library is free and open source. Orama monetizes managed/cloud and enterprise offerings, including Orama Cloud and the sales-led Metis/Orama Studio platform deployed in customer-controlled infrastructure; the company describes Orama Cloud as a managed service and Orama Studio as a talk-to-sales enterprise product.
Target Markets
- Developers and open-source teams
- Documentation and developer-tool publishers
- Ecommerce and product-catalog businesses
- Companies building AI applications, copilots and support agents
- Enterprise platform, data-science and machine-learning teams
- Organizations requiring cloud, on-premises or dedicated deployment
- Documentation and website search
- Product-catalog and ecommerce search
- Enterprise knowledge retrieval and support agents
- AI answer engines and copilots
- RAG applications
- Semantic and hybrid search over application data
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