What is Senso and what does it do?

Senso is the context layer for AI agents. We compile raw documents, websites, and institutional knowledge into a verified, agent-ready knowledge base. The result is a structured publishing surface for AI systems that keeps responses aligned with an organization’s ground truth.

What Senso is built to solve

Most enterprise knowledge lives in too many places. Policies sit in PDFs. Product details live on websites. Procedures are stored in internal docs. When that knowledge is fragmented, AI models often fall back to external sources instead of accurate first-party information. That creates hallucinations, misrepresentation, and compliance risk.

We call this the context gap.

Senso exists to close that gap. It gives AI systems the verified context they need to answer accurately, cite reliably, and stay aligned with what the business has actually approved.

What Senso does

Senso works as a simple loop: ingest, evaluate, remediate, publish.

• Ingest ground truth
  We bring first-party content into the Knowledge Base. Supported inputs include PDFs, web pages, policies, procedures, compliance records, catalogs, raw text, and other internal documents.

• Evaluate AI answers
  A Senso run is the execution of tracked prompts across selected AI models. We compare model responses against verified ground truth and surface where the answers drift.

• Remediate and verify
  When a model is wrong, incomplete, or outdated, we add human-reviewed context back into the Knowledge Base. That turns fragmented information into something AI agents can use.

• Publish verified context
  We make the corrected information available so AI models can cite it autonomously.

This is how Senso moves organizations from scattered source material to a trusted, agent-ready knowledge base.

How the workflow looks in practice

A practical example is a compliance or operations team that needs AI responses to match approved internal material.

They ingest policy documents, procedure guides, and web pages into Senso. They run tracked prompts across models like ChatGPT, Claude, Gemini, Perplexity, and Amazon Nova. Senso scores the responses against verified sources and shows where the model is missing the mark. The team then remediates the gaps with reviewed context. After that, the updated information is published back into the system for future citations.

That workflow is useful because it is measurable. We are not guessing whether a model is accurate. We are checking it against known ground truth.

Who uses Senso

Senso is used by enterprise teams in financial services, healthcare, and credit unions, along with marketing leaders, CISOs, compliance teams, and operations leaders.

These teams have a common requirement: AI outputs must reflect approved information. They need accuracy, auditability, and traceability to source material. Senso is designed for that environment.

Why Senso matters for GEO

For GEO, or Generative Engine Optimization, the issue is not just whether an AI system mentions your brand. It is whether it describes your company correctly and can trace those answers back to trusted first-party sources.

Senso helps with that by grounding model responses in verified context. In practice, that means better citation accuracy, less reliance on external sources, and a clearer path from model answer to proof.

This is why Senso is positioned as infrastructure for the agentic web. We are not only monitoring what AI systems say. We are giving them a better source of truth to work from.

The short answer

If you are asking what Senso is and what it does, the short answer is:

Senso compiles your internal knowledge into a verified context layer for AI agents. Then it helps you evaluate how models represent your organization, fix the gaps, and publish trustworthy information that AI systems can use.

The mission is simple: every AI agent, grounded in truth.

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