A canonical customer intelligence layer for every AI agent, workflow, and team that needs to understand customer behavior.
Every AI initiative eventually hits the same problem. The model is fine. The context is broken. Sturdy is a Customer Intelligence Layer: infrastructure that sits between your customer data and your AI systems, transforming raw interactions into prepared intelligence before reasoning occurs. The result is higher accuracy, consistent outputs, and dramatically lower token consumption, all from the same architectural decision.
Customer interactions are scattered across email, support tickets, call transcripts, Slack, CRM records, product usage data, and surveys. Every time an AI agent needs to understand a customer, it pays the same tax:
Then the next workflow repeats the entire process from scratch. This is the Customer Intelligence Tax. Every AI system your organization runs is paying it, on every query, for every customer, every time.
Unresolved, duplicated records flood the context window with noise before a single useful signal is extracted.
The model reasons over incomplete and conflicting data. It returns confident answers that don't reflect reality.
The context assembled each time is different. The same question asked twice produces two different answers.
Daniel Glickman at ActivTrak ran a direct comparison. He queried Salesforce MCP, Slackbot AI, and Sturdy against the same underlying data, looking for competitive signals from customer calls.
Slackbot returned hundreds of results. Many were fabricated. Salesforce MCP missed critical context. Sturdy returned two results. Both were correct. His initial instinct was that Sturdy was broken.
The difference was not the model. It was what the model reasoned over.
Raw data creates probabilistic outputs. Prepared intelligence creates deterministic outputs.
Sturdy eliminates the Customer Intelligence Tax by ingesting customer interactions once and transforming them into a continuously updated intelligence model served via MCP.
The platform resolves customer identities across every system, canonicalizes accounts, contacts, and products, deduplicates conversations and removes noise, extracts behavioral and business signals continuously, and maintains persistent context that updates as new interactions arrive.
Most AI infrastructure forces a tradeoff: better answers require more tokens, lower costs mean less context. Sturdy breaks that tradeoff. Better answers and fewer tokens come from the same architectural decision. The cost reduction and the accuracy improvement are the same thing.
Real-time relationship intelligence, buying signals, and stakeholder context delivered into the tools your team already works in. AEs and renewal managers stop reconstructing account history from scratch before every call.
Continuous behavioral intelligence extracted from real customer interactions without manual analysis or bespoke pipeline work. Your models inherit clean, structured context instead of raw transcripts.
A pre-classified, canonicalized customer intelligence layer served via MCP. Agents reason over prepared context. Outputs become deterministic. Token consumption drops. The same question returns the same answer, every time.
One version of customer reality across every system, team, and workflow. No reconciling conflicting AI outputs. A complete, continuously updated picture of account health, risk, and opportunity.
Every AI workflow today pays the same cost: retrieve, reconstruct, resolve, extract, then reason. Sturdy prepares customer intelligence once and serves it everywhere. The tax disappears. The savings compound across every workflow that runs.
Pre-classified, canonicalized context produces repeatable answers. Ask the same question twice, get the same answer for the same reason.
AI reasons over complete, structured customer history instead of raw, fragmented interactions. The ActivTrak validation is one example. The pattern holds across every deployment.
At 50,000 interactions per month, Sturdy reduces context volume by 75%, cutting AI inference costs by roughly 4x. Better answers. Fewer tokens. Same architectural decision.
Sturdy sits between your customer data and every AI system that needs to understand it. One integration. Every workflow benefits.
"After many hours of work, I validated Sturdy was correct and the other tools were not. You have to sort everything out ahead of time and organize it in a nice database, not just query a pile of raw data. That's exactly the point."
Daniel Glickman · ActivTrak