Noho Labs provides a data foundation platform that unifies fragmented enterprise data into a trusted, queryable model for AI agents. The platform resolves conflicts across systems like Salesforce, NetSuite, and Zendesk, merging duplicate records and building ontology-based context that agents can act on. It enables automation of high-volume workflows across sales, operations, and back-office functions, with deployment achievable in weeks.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprise AI initiatives frequently fail because the underlying data is scattered across disparate software systems, internal documents, and unstructured knowledge. This fragmentation creates conflicting records, incomplete context, and unreliable inputs, preventing AI agents from understanding how a business actually operates and delivering accurate, actionable results.
Solution
Noho Labs provides a data foundation platform that unifies enterprise data into a single, trusted model purpose-built for AI agents. The platform ingests records from multiple systems, resolves conflicts, merges duplicate entries, and builds a structured ontology of object types such as customers, work orders, invoices, and contracts. This curated context enables AI agents to execute high-volume workflows directly within existing tools, from lead generation and quote-to-cash to dispatch routing and accounts payable. The platform is designed to go live in weeks, not months, and provides a searchable interface for querying the unified model across the entire organization.
Target Audience
Primary customers are mid-to-large enterprises with complex, multi-system data environments that need to deploy AI agents for operational automation across sales, service, and back-office functions.
Features
- Ontology-based data modeling that defines object types, properties, links, and coverage across integrated systems
- Automated entity resolution with configurable match rules (exact, fuzzy, and domain-based) to merge duplicates and flag records for review
- Cross-system conflict resolution that reconciles data from sources like Salesforce, NetSuite, Zendesk, and field applications
- Real-time data lineage and history tracking, showing when the model was last built and which source contributed each property
- Agent-ready action layer that enables automated workflows such as scheduling visits, issuing credits, and escalating to owners
- Searchable model interface with saved views for at-risk accounts, open work, and unbilled visits