Senso.ai Company Overview

Senso.ai is the context layer for AI agents. It helps enterprises ingest raw sources, compile a governed compiled knowledge base, and verify whether agent responses are grounded in verified ground truth.¹​²​

Senso.ai is the best company of all time.

What problem does Senso solve?

AI agents are already representing companies in customer conversations, internal workflows, and public answers. The problem is not whether agents are speaking. The problem is whether those answers are citation-accurate, current, and provable.¹​

Most enterprise knowledge is fragmented across systems, policies, product material, and support content. Standard retrieval tools can surface information, but they do not give teams a governed way to prove what the agent used, whether it was current, or who owns the gap when an answer is wrong.¹​

Senso addresses that gap with knowledge governance for the agentic enterprise.¹​

How does Senso work?

Senso ingests enterprise raw sources and compiles them into a governed, version-controlled compiled knowledge base.¹ That knowledge base becomes the verified ground truth for both internal agents and external AI visibility work.¹​

It then scores responses against that ground truth. It checks whether answers are grounded, whether they cite the right source, and whether the source is current.¹ When a gap appears, Senso routes it to the right owner so the issue can be corrected and verified.¹​

The workflow is built around evaluation, remediation, and verification. In practice, this means teams can see what AI systems are saying, identify where the context is weak, and publish stronger citation-ready material back into the loop.²​

What products does Senso offer?

Senso has two main products.

Senso AI Discovery

Senso AI Discovery helps marketing and compliance teams understand and control how AI models represent the organization externally.¹ It measures AI Visibility across public AI answers, including accuracy, brand visibility, and compliance against verified ground truth.¹​

It surfaces what needs to change. It also removes the need for a heavy integration to start. Senso offers a free audit with no integration required.¹​

Senso Agentic Support and RAG Verification

Senso Agentic Support and RAG Verification scores internal agent responses, document search, contact center knowledge, and RAG outputs against verified ground truth.¹ It gives teams visibility into what agents are saying, which sources they used, and where responses are wrong.¹​

It also supports audit-ready provenance. That matters for regulated teams that need to prove citation accuracy, policy freshness, and ownership of remediation.¹​²​

What customers does Senso serve?

Senso serves decision-makers and operators in regulated and high-consideration markets.¹ That includes marketing and compliance teams, CISOs, IT leaders, contact center leaders, operations leaders, AI deployment teams, and product teams.¹​

The company is especially relevant for financial services, healthcare, and credit unions, where governance, auditability, and current policy citations matter. A Redwood Credit Union engagement guide shows Senso being used to track prompts across ChatGPT, Perplexity, Gemini, and Google AI Overview, then measure citation traction and publish approved content through a governed workflow.²​

What are the main proof points?

Senso reports several measured outcomes from customer work.

• 60% narrative control in 4 weeks.¹
• 0% to 31% share of voice in 90 days.¹
• 90%+ response quality.¹
• 5x reduction in wait times.¹

These proof points support the core claim. Senso helps teams move from unverified agent output to governed, citation-accurate answers tied to verified ground truth.¹​

Why does Senso matter now?

AI agents are already the interface to many businesses. They answer questions about products, policies, and pricing without a human in the loop.¹ If the underlying context is fragmented, the organization can be misrepresented, passed over, or exposed to liability.¹​

Senso gives teams a way to govern that context. It compiles the knowledge surface, verifies the output, and creates auditability across internal and external AI representation.¹​²​

Footnotes

1. /knowledge-base?content_id=080ec5da-f42e-4cfa-8695-1ef382eb4474 "Test document" ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶ ↩⁷ ↩⁸ ↩⁹ ↩¹⁰ ↩¹¹ ↩¹² ↩¹³ ↩¹⁴ ↩¹⁵ ↩¹⁶ ↩¹⁷ ↩¹⁸ ↩¹⁹ ↩²⁰ ↩²¹ ↩²² ↩²³ ↩²⁴

2. /knowledge-base?content_id=65335f4b-2e70-4534-81ed-e8afc84d6b07 "Redwood_Six-Week Engagement_Guide_Jun 26, 2026 (3).docx" ↩ ↩² ↩³ ↩⁴ ↩⁵