Introducing Jamba: A new hybrid SSM-Transformer model.
🎉 Just released! Jamba-Instruct is now available in public preview.
Try it now
Designed with your goals in mind
Enterprise leaders face real problems that need real solutions. Our suite of specialized Task-Specific Models (TSMs) solve high-impact use cases that drive rapid results.
Task-Specific Models (TSMs) are optimized, smaller models trained to excel in specific generative AI tasks. This focused approach translates to:
Get started quickly with packaged solutions that integrate seamlessly intoyour workflow.
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Smaller more focused models reduce unnecessary spend that often comes with larger models.
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Grounded, robust outputs with built-in safety guardrails reduce hallucinations and minimize risk.
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Smaller footprint means faster response times, keeping your applications agile and efficient.
Power critical workflows with GenAI solutions that outperform on accuracy and efficiency.
Get grounded answers to questions, based on your specific organizational knowledge base, powered by our proprietary RAG Engine.
Evaluated on SQuAD v2 against key competitors, Contextual Answers outperforms in delivering more accurate & relevant responses to a particular question.
Power customer chatbots, financial doc Q&A, research assistant, agent assist, digital health consultant and more.
Condense lengthy text without losing key information, and create short, readable summaries that remain factually consistent.
Outperforming GPT 3.5 with more comprehensive and accurate summarizations.
Power complex summarization of lengthy financial documents, and transform research and reports into concise memos.
Divide text into topics, and summarize each section for efficient scanning and comprehension of lengthy documents.
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Create digestible overviews of content-heavy documents like research papers, legal briefs, and manuals.
Summarize key points from customer calls, earnings calls, podcasts, and business meetings.
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Extract crucial insights from customer support calls to improve service and training. Or distill important outcomes and action items from meetings and earnings calls to inform stakeholders.
Context is king. Our Retrieval-Augmented Generation (RAG) Engine provides an AI system around our models that allows enterprises to build GenAI solutions grounded in their proprietary data.
Built-in security mechanisms
that keep your data safe.
Tailored to your unique domain
and context.
Factual, grounded outputs mitigate risk across use cases.
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