Frequently asked questions

Riley is the Business Context Platform that transforms fragmented enterprise data into trusted business context for people and AI.

It connects your CRM, customer conversations, product usage, internal documents, databases, and other business systems into a single AI-ready context layer that powers more accurate reasoning, automation, and decision-making across your organization.

Riley helps organizations make better decisions by giving every employee and AI system access to complete business context.

Teams use Riley to understand customer health, prioritize accounts, identify expansion opportunities, detect churn risk, answer business questions, power internal AI assistants, and automate workflows—all using information connected across the business, not isolated systems.

Because a general-purpose model has no way to know what your business means by its own terms. It can read whatever data you expose to it, but it does not know which records refer to the same customer, how your company defines “active customer” or “churn”, which number is current, or what was actually said on last quarter's calls.

The failure is rarely a blank answer. It is a confident one, assembled from whichever rows the model happened to retrieve. Two people asking the same question in different words can get two different numbers, and neither can tell which one is right.

Fixing it means supplying what the model is missing: resolved entities, governed definitions, current data, and the unstructured record joined back to accounts. That is the layer Riley maintains.

Accuracy on company data comes from four things a model cannot supply on its own: one resolved identity per customer across every system, a single governed definition for each business metric, data fresh enough to be current at the moment of the question, and access to unstructured sources like calls and tickets joined back to accounts.

Prompt engineering and larger models do not move any of the four. They change how an answer is phrased, not what it is grounded in. Neither does a data cleanup project on its own, which improves the inputs but leaves every AI tool to reinterpret them separately.

Riley maintains those four as a business context layer, so every AI tool reasons over the same governed facts and cites the records it used.

MCP solves access, not agreement. It gives a model a live connection to your systems, which genuinely helps with reach and freshness — a live query beats last night's batch, and connectors reach systems that were previously unreachable.

But MCP carries no concept of a resolved account key and no shared glossary. The model still has to guess how to join your systems, and it guesses differently on each query. Two sessions can produce two different customer counts, both citing real data.

Riley sits behind MCP rather than replacing it. The assistant keeps its connection, and the entities, definitions, and lineage come from a governed context layer instead of being re-invented per question.

Claude, ChatGPT, Gemini, and other LLMs are excellent reasoning engines—but they don’t know your business.

Riley gives them that knowledge.

Riley continuously builds and maintains your company’s business context so AI can reason using your customers, products, revenue, historical decisions, and internal knowledge—not just general information.

Many organizations use Riley as the business context layer for Claude, OpenAI, and other AI platforms through MCP, making their existing AI significantly more accurate and useful.

Yes.

Riley ingests, cleans, and organizes both structured and unstructured data—including CRM systems, databases, spreadsheets, documents, PDFs, customer conversations, product usage, support tickets, websites, and internal knowledge.

Even fragmented or inconsistent data is transformed into trusted business context that AI can understand and reason over accurately.

You can connect data through pre-built integrations, managed sync, our API, or simple file uploads.

Most data sources can be connected in minutes using Riley’s pre-built integrations or managed sync.

For custom systems or more complex enterprise environments, our deployment team typically has customers up and running within 24 hours.

Yes.

Riley is built for enterprise deployments and is SOC 2 Type II and GDPR compliant. We also support enterprise features including Single Sign-On (SSO), role-based access controls (RBAC), audit logs, and private deployments for organizations with advanced security requirements.

Your data is never shared across customers or used to train public AI models.

Riley continuously maintains business context across your organization so AI always reasons using your latest business knowledge—not just the prompt you provide.

Every answer is grounded in your own data and includes citations back to the original source, giving users complete transparency and confidence in every recommendation.

No.

Riley works alongside your existing technology stack. It connects your CRM, data warehouse, documents, conversations, and business systems to create a trusted business context layer that powers AI and natural language search.

Your existing systems remain the source of truth—Riley makes them understandable and actionable for both people and AI.

Riley is priced based on the volume of data ingested and platform usage—not by the number of users.

Every plan includes unlimited seats, allowing your entire organization to access trusted business context without per-user licensing costs. We offer flexible plans for organizations of all sizes.

You can start a free trial by connecting your data sources and exploring Riley on your own business data, or schedule a personalized demo with our team to see how Riley can support your specific use cases.