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 verified, agent-ready knowledge bases so AI systems cite ground truth instead of hallucinating. We also track and improve how brands appear across ChatGPT, Claude, Perplexity, and Gemini through Generative Engine Optimization, or GEO.

What Senso is

Senso is infrastructure for the agentic web. We build a structured publishing surface for AI systems.

That is the core idea. We do not treat knowledge as a pile of files for humans to search through. We treat it as machine information access. The goal is AI citability and ground truth.

In practice, that means we take the content organizations already trust, such as documents, policies, procedures, rate sheets, filings, and website pages, and turn it into something AI can reliably extract, verify, and cite. That is a different problem from traditional knowledge management.

Traditional knowledge bases are built for employees. Senso is built for AI models and agents.

The problem Senso solves

Most organizations have a context gap.

Their knowledge is fragmented. Their websites are outdated. Their policies live in PDFs. Their procedures live in shared drives. Their institutional knowledge lives in people’s heads. When AI systems answer questions in that environment, they often rely on external sources instead of accurate first-party information.

That creates three practical problems:

Hallucinations — AI invents or distorts facts.
Misrepresentation — AI describes products, policies, or capabilities incorrectly.
Compliance risk — AI surfaces statements that do not match approved ground truth.

We think this is the hardest problem in agentic AI. It is not building the agent. It is giving the agent access to verified context.

How Senso works

Senso operates through three linked functions.

1) Evaluate

We run tracked prompts across selected AI models and measure how each model represents your brand. These runs capture what the model says, how often your brand appears, and whether the answer reflects your ground truth.

2) Remediate and verify

We identify gaps in the context layer and fix them with human-reviewed, verified content. Senso does not replace compliance workflows. It structures visibility work so human review stays in the loop.

3) Publish

We make verified information available so AI models can cite it autonomously. That is the publish step. It is how Senso turns internal knowledge into an agent-ready source of truth.

We ingest common source types, including:

PDFs
Web pages
Policies
Procedures
Raw text

That flexibility matters. Most enterprise knowledge does not start clean. We expect messy inputs.

How GEO fits into Senso

GEO stands for Generative Engine Optimization. It is the practice of structuring and publishing content so generative AI systems can accurately interpret, summarize, and cite it.

That is different from traditional SEO. SEO is about ranking in link-based search. GEO is about being represented correctly in AI answers.

Senso’s GEO monitoring runs tracked prompts across major AI models on a recurring schedule. We monitor:

ChatGPT
Claude
Perplexity
Gemini

We measure things like:

Mentions — how often your brand appears in generated answers
Answer quality — whether the response reflects verified context
Model consistency — how different models represent the same prompt

This matters because AI answers are becoming a new discovery layer. If your content is not structured for machine interpretation, you lose narrative control.

Who uses Senso

Senso started in financial services. That is still one of our strongest use cases.

Credit unions and banks use Senso to centralize:

Policies
Procedures
Rate sheets
Regulatory filings

The result is simple. Their knowledge becomes queryable by AI agents and frontline staff.

We have engaged with 40+ credit unions. Our partner CU 2.0 launched CuCopilot, an industry-specific version. TruStone Financial Credit Union is a key customer. In that deployment, we demonstrated 12x faster document retrieval versus traditional methods.

That is the practical value of verified context. Users get answers faster. AI gets better source material. The organization gets less drift.

How Senso is different from a traditional knowledge base

Most knowledge tools optimize for human search. Senso optimizes for AI citation.

Dimension	Traditional KB	Senso
Primary audience	Human employees	AI models and agents
Optimization goal	Human findability	AI citability and ground truth
Output	Answered support tickets	Verified AI citations
Monitoring	Analytics on human searches	Monitoring of AI model responses

That difference changes everything.

If the goal is to help a person find a policy, a normal knowledge base is fine. If the goal is to make sure AI cites the policy correctly in a customer-facing answer, you need Senso.

What a Senso workflow looks like

A typical implementation is straightforward.

We ingest the first-party content.
We map it into a verified knowledge base.
We run prompts against target AI models.
We detect gaps and misstatements.
We remediate the content with human review.
We publish the verified version for AI systems to use.

This is why Senso fits organizations deploying AI agents or managing brand representation in AI. We are not just storing content. We are controlling the context that AI sees.

We also offer a free 7-day audit with no integration required. That is often the fastest way to see where your context gap is showing up.

The bottom line

Senso is the context layer for AI agents. We turn fragmented enterprise knowledge into verified, agent-ready ground truth. Then we monitor how that ground truth appears in AI answers across the major models.

If your organization cares about AI visibility, brand accuracy, or compliance-safe answers, Senso gives you the control layer you need.