Kaliper provides AI‑driven agents that automate the manual tasks of manufacturing supply chains, consolidating data from emails and disparate systems into a single source of truth. 5%, and freeing cash tied up in excess inventory.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturing supply chains rely on manual processes, with critical information scattered across countless emails and legacy systems, preventing a unified view of operations. This fragmentation forces skilled staff to spend the majority of their time on repetitive, data‑entry tasks instead of strategic decision‑making.
Solution
Kaliper delivers AI‑native agents that act as virtual team members, automatically ingesting and consolidating data from emails, ERP, and other disparate sources into a single source of truth. The agents continuously monitor the supply‑chain workflow, detect anomalies, and initiate communication to resolve issues before they impact delivery schedules. By handling up to 95% of repetitive, technical work, the platform frees human operators to focus on higher‑value decisions that improve on‑time delivery, reduce cost of goods sold, and free cash tied up in excess inventory. Interaction with the agents requires no new software; users simply write to the agent as they would to a colleague, and the AI reads the thread, executes actions, and updates the system in real time.
Target Audience
Primary customers are manufacturing operations teams and supply‑chain managers at mid‑size to large producers who need to streamline data handling and accelerate issue resolution across complex, multi‑system environments.
Features
- AI agents that parse and reconcile data from emails, ERP, and other supply‑chain systems without manual entry
- Automated problem detection and resolution workflows that notify relevant stakeholders through familiar communication channels
- Real‑time consolidation into a unified dashboard, providing a single source of truth for demand, production, and delivery status
- Natural‑language interface allowing users to interact with agents via standard messaging tools, eliminating the need for new platforms
- Continuous learning models that improve accuracy of issue identification and recommendation over time