Invisible Technologies provides an AI‑driven automation platform that ingests raw data, runs machine‑learning models, and orchestrates end‑to‑end workflows without human intervention. The low‑code solution offers pre‑trained industry models and standard APIs for seamless integration, enabling large enterprises and labs to automate high‑volume data processes, improve accuracy, and scale securely across regulated sectors.
Funding
$34.9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
VCFounders
Product
Problem
Enterprises and labs often rely on manual, repetitive data‑processing workflows that are slow, error‑prone, and require specialized staff, limiting scalability and delaying insight delivery.
Solution
Invisible Technologies offers an AI‑driven automation platform that ingests raw data, applies machine‑learning models, and orchestrates end‑to‑end workflows without human intervention. The system can be customized for specific domains—such as contact‑center analytics, demand forecasting, back‑office processing, and computer‑vision tasks—while exposing standard APIs for integration with existing tools. By handling data extraction, validation, and analysis in a unified cloud environment, the platform delivers faster, more accurate results and frees staff to focus on higher‑value activities. Built with modular building blocks, the solution scales from pilot projects to enterprise‑wide deployments and supports secure, auditable operations across regulated industries.
Target Audience
Primary customers are large enterprises and institutional labs in sectors such as banking, asset management, public‑sector agencies, energy, healthcare, and life sciences that need to automate high‑volume, data‑intensive processes.
Features
- End‑to‑end AI workflow engine that automates data ingestion, transformation, model inference, and output routing
- Pre‑trained industry models (e.g., compliance risk scoring, demand forecasting, visual inspection) with easy fine‑tuning on proprietary data
- Low‑code integration layer offering REST/GraphQL APIs, SDKs, and FHIR‑compatible connectors for seamless embedding into existing systems
- Scalable cloud architecture with auto‑scaling compute, role‑based access control, and end‑to‑end encryption for data security and compliance
- Real‑time monitoring dashboard that provides performance metrics, error alerts, and audit trails for operational transparency
- Continuous model management tools for versioning, drift detection, and automated retraining to maintain accuracy over time