Discover how AI agents are reshaping the manufacturing operating model
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Automate supplier quote comparison for faster, data-driven decisions
Manually consolidating and comparing supplier quotes is slow and error-prone. Kavida’s agent automatically compares validated quotes — generating sourcing board summaries and decision-ready insights for faster, fairer supplier selection.
Manual quote comparison leads to missed savings and poor supplier decisions
Disjointed, manual consolidation
Teams combine quote data from PDFs, spreadsheets, and emails — time-consuming and prone to inconsistency.
Misses best-value options
No clear comparison view leads to bias, and it’s difficult to benchmark suppliers fairly or spot the best value quickly.
Limited visibility to risk
Manual comparison misses supplier risks like delivery reliability, performance history, or exposure to external factors.
Agent PO structures all validated quotes and builds an instant side-by-side comparison — complete with supplier metrics, risk indicators, and decision-ready summaries.
Automatically aggregates pricing, lead times, and terms from validated quotes into a standardised dataset.
Builds a clear visual comparison of all suppliers across cost, delivery, and commercial performance.
Identifies suppliers with exposure to delivery issues, performance variability, or market disruptions.
Creates ready-to-share summaries and visuals that help stakeholders make faster, more transparent sourcing decisions.
Key capabilities that drive results
Clear quote comparison
Displays all validated supplier quotes in a unified view across price, lead time, and key commercial terms.
Identifies external risk exposure
Identifies suppliers with potential external risks, and allows users to query the agent for deeper insights.
Sourcing board generation
Builds sourcing board summaries and visuals combining delivery reliability, cost, and risk exposure for decision-making.
What moves the needle for your business
Shorter sourcing cycle times
Automated quote comparison and reporting reduce time-to-award, helping teams respond faster to business demand.
Data-backed sourcing strategy
Aggregated comparison data builds institutional knowledge — enabling smarter, long-term category and supplier strategies.
Reduced cost of goods sold
Standardised comparisons ensure the most cost-effective supplier is chosen without compromising quality.
Patti Humphreys
More applications of AI agents for manufacturers
The agent assembles RFQ packs with drawings and specs, tailoring drafts for each supplier.
The agent tracks supplier responses, flags delays, and follows up to keep RFQs on schedule
The agent reads supplier quotes, extracts structured data, and validates
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