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Deep Research: Sapience can help you create a deep research AI Agent rapidly. It comes with a Deep Web Research agent out of the box, with no set up required.

You can also build your own Deep Research Agents, coupling web-based research with internal data from just about any source.

A Deep Research agent uses Agentic RAG, or multi-step reasoning plus researching to analyze huge amounts of data through a particular research lens to give you reliable answers to your advanced questions, on demand, all the time.

Private Data: Deep Research agents from OpenAI and Google are interesting for doing internet research, but 90% of a company's data is private. AI Studio unlocks the power of multi-step agentic RAG research across all your data stores.

Data Sprawl: In all but the smallest organizations, the amount of information stored in structured and unstructured data is vastly more than even the best knowledge-worker can keep in their head.

Negative Impact: Navigating many internal systems to find the right information at the right time is extremely difficult. This has a meaningful negative business impact: it slows decision making, slows customer service, hinders sales conversion, and in some cases leads to bad decisions occurring or negative customer outcomes.

AI + Hallucinations: Many generations of technology have sought to address this cluster of problems, but modern LLM's are the most powerful tool we've ever had for this use-case. AI's ability to ingest, understand, and summarize vast quantities of information in response to queries is well known. However, hallucinations represent a major impediment to the mass-adoption of AI knowledge systems. Solution: Using a Retrieval Augmented Generation (RAG) architecture, coupled with fine-tuning and guard-rails, you can build the perfect internal knowledge resource for your business, that has access to exactly the right content at the right time, backed by drill-through to source data where the user has appropriate permissions. RAG systems can connect to line-of-business systems, and are 'grounded': they don't make things up, and if done properly provide transparency to the user about the data-source relied upon in the answer to a given query.

No technology tool that has come before has enabled the productivity gains that generative AI does for access to all your company's knowledge across both structured and unstructured data-sources.

If you're looking to understand how to tackle knowledge-management with AI, get in touch.