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Retrieval That
Cites Its Sources

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Empower your AI with trusted knowledge.
Eagna’s Retrieval-Augmented Generation (RAG) platform connects your private data with powerful search and grounding capabilities — ensuring every answer is accurate, explainable, and verifiable.

Highlights

  • End-to-End Pipelines: Load content from PDFs, Office docs, HTML, and databases with automatic chunking and metadata tagging.
  • Smart Search:Combine vector search, BM25, and hybrid retrieval with rerankers and cross-encoders for precision.
  • Source Transparency: Every response includes citations and snippets for user trust and auditability.
  • Always Fresh: Scheduled syncs, incremental indexing, and per-source access controls keep your knowledge up to date.
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Specs

01. Throughput

1,000+ tokens per minute per node (model-dependent)

02. Latency

p95 < 300ms (7B/13B models)

03. Resilience

Multi-AZ failover, auto-healing pods, and pod disruption budgets

Frequently asked questions

No. The platform runs in your VPC/on-prem. Data, prompts, and outputs stay within your perimeter.

Llama 3.x/4, Mistral family, Falcon 40B/180B, Jais, ALLaM, Fanar, StarCoder2, Code Llama, and more. Bring your own weights.

Yes. We support offline registries, license mirrors, and fully disconnected operation.

We offer a GCC Localization Pack featuring Arabic-centric models (Jais/ALLaM/Falcon Arabic), dialect evals, and Arabic UI.

Software subscription + optional services; infrastructure is separate and transparent. We provide TCO models and right-sizing.

Yes—up to 24×7 with 1-hour P1 response and availability targets aligned to your HA design.

Empowering Enterprises with Private Intelligence.

Address

Office 6, Unit 28, Orchard House, Glenrock Business Park, Ballybane, Galway, H91 YH7D, Ireland

Say Hello

info@eagnatech.ai

+353 91 455 202

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