The Context Layer
Before any AI runs, Sturdy builds a clean understanding of every account.
ML-driven deduplication orchestrates accounts and contacts across CRM, email, transcripts, tickets, and chat into a single canonical record.
The data layer AI inference deserves.
Sturdy's Data Rails solves three problems most enterprise data platforms ignore: entity identity across silos, high-fidelity semantic retrieval, and access control enforced at the data layer — not in application code.
The Problem
Three problems. One infrastructure layer.
Enterprise AI deployments fail at the data layer, not the model layer. Sturdy Data Rails is purpose-built to fix that before any LLM call is made.
Cross-silo canonical identity
The same person is five different strings across email, CRM, Slack, and Zoom. Sturdy resolves them deterministically — not with fuzzy confidence scores — into a single canonical node with full alias coverage.
High-fidelity semantic retrieval
Off-the-shelf embeddings trained on web text don't understand account names, deal terminology, or the specific phrasing patterns of enterprise communication. Sturdy's domain-fine-tuned retrieval stack is built for this corpus.
Permissions at the data layer
Application-layer permission checks are brittle. A missing if-statement in a new code path creates exposure. Sturdy enforces access control as a mandatory predicate on every index query, below all application logic.
Our Solution
A purpose-built data layer for AI over enterprise communication.
Sturdy ingests every silo, resolves entities into a canonical graph, pre-classifies content into retrievable units, and exposes hybrid search with permissions enforced at query time. Every stage consumes the same normalized stream — no application code reaches around the rails.
The Outcome
Deliver AI outcomes cheaper, better, and faster.
Not a chatbot guessing from a fine-tune. Real account intelligence, drawn from every email, ticket, call, and CRM record - surfaced in seconds.
What the AI knows before you ask your first question
Account identity
Key contacts & roles
Relationship history
Engagement patterns
Sentiment over time
Risks & blockers
Expansion signals
Platform
Three layers. One contextual object.
01 — Consolidate
Ingest and normalize across every silo
CRM, support, email, chat, calls — unified into a single customer entity model. Accounts resolved. Contacts mapped. Language attributed. A clean foundation AI can actually reason over.
02 — Identify
AI that runs on a model it understands
Accurate, attributable account intelligence — grounded in what customers actually said. Risks, opportunities, and relationship signals surface early, across your entire book of business.
03 — Act
Role-based intelligence, where teams work
CS, Sales, Renewals, Product, and Leadership each get the slice of account intelligence relevant to their job — in the tools they already use. What a customer said becomes what a team does.
Built for Every Team
Start with no code on day one. Build anything when you're ready.
No-code, day one
Value before you write a line.
Account reviews, QBR summaries, risk signals, and role-based updates — all in plain language, from the moment you connect your systems. No SQL. No dashboards. No data team.
Open data layer
Your LLM, apps, and data.
Plug any LLM into Sturdy's normalized customer data via API and build the account intelligence tools your business actually needs — instead of renting ones built for someone else.
Works with any LLM
Open AI
Anthropic Claude
Google Gemini
Mistral
Llama
Azure OpenAI
FUD-Free Zone
You should know exactly what your AI is doing with customer data. With Sturdy, you always do.
Connect what customers say to why your numbers move. Contextual revenue intelligence, ready for any LLM — or running natively in Ask Sturdy from day one.
Full Data Vsibility
See exactly what's going into the AI — and exactly what's coming out.
Sturdy gives every user a dedicated interface to inspect the data flowing in and out of the models in real time. You can see which customer conversations, records, and signals are being used to generate each piece of intelligence — and trace every insight back to its original source.
