Knowlestry offers an industrial business intelligence platform that consolidates expert tacit knowledge and machine‑generated data into a secure, self‑learning knowledge hub. A natural‑language interface and AI‑driven assistant enable users to query the unified source for real‑time dashboards, anomaly detection, and predictive insights without deep technical expertise. The solution includes role‑based security and an extensible API for custom applications in manufacturing and process engineering.
Funding
Funding not disclosed
Founders
Product
Problem
Industrial enterprises often lose valuable tacit expertise and struggle to combine that knowledge with machine-generated data, resulting in slow AI/ML adoption, limited anomaly detection, and suboptimal process optimization. The lack of a unified, searchable knowledge source hampers collaboration between domain experts, analysts, and automated systems.
Solution
Knowlestry delivers an industrial business intelligence platform that centralizes both explicit and tacit domain knowledge into a secure, self‑learning knowledge hub. By integrating this hub with machine data pipelines, the platform enables context‑aware analytics, accelerating use cases such as anomaly detection, quality assurance, and parameter optimization. Users interact through a natural‑language interface that queries the single source of truth, generating actionable insights, dashboards, and ad‑hoc reports without requiring deep technical expertise. An AI‑driven agent assists in data curation, feature engineering, and pipeline construction, while the platform’s API allows custom applications for training, onboarding, and technical support. Continuous LLM fine‑tuning and token‑usage optimization ensure high‑quality outputs while protecting intellectual property.
Target Audience
Primary customers are manufacturers, process engineers, and operations teams in heavy‑industry sectors who need to operationalize expert knowledge and accelerate AI‑driven optimization, as well as data science groups seeking a secure, domain‑enriched analytics environment.
Features
- Centralized Knowledge Hub that captures, curates, and links tacit expertise with structured machine data
- Natural‑language query interface delivering real‑time answers, dashboards, and reports from the unified knowledge base
- AI agent for assisted data fusion, pipeline generation, and feature engineering tailored to specific industrial use cases
- Context‑sensitive machine‑data analysis that combines generative AI with domain‑specific knowledge for precise anomaly detection and predictive modeling
- Secure, role‑based access and IP protection built into the platform architecture
- Extensible API for building native or third‑party applications such as training simulators, onboarding tools, and customer‑support bots
- Self‑learning LLM layer that continuously adapts outputs, optimizes token consumption, and maintains output quality at scale
- Access to aggregated industry benchmarks and best‑practice knowledge for cross‑organizational learning