Mithra
Mithra-Ai provides a cognitive spend intelligence platform that uses AI agents to cleanse, classify, and enrich procurement data, creating a trusted foundation for identifying savings opportunities. The platform's Opportunity Agents surface actionable findings ranked by value and confidence, while the Atlas copilot enables users to ask questions and generate board-ready reports, helping procurement teams convert insights into realized savings.
- Data & Analytics
- AI Agents
- Artificial Intelligence
- Enterprise Software
- Software Only
Funding
Raised to date
$325KRaised 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.
across 1 round
$325K · Seed
Announced Jan 2023
Disclosed cumulative: $325K
Founders
Product
Problem
Procurement teams struggle with fragmented and inconsistent spend data, making it difficult to identify cost-saving opportunities and optimize supplier relationships. Manual data cleansing and classification are time-consuming and prone to errors, hindering effective decision-making.
Solution
Mithra-Ai provides a Cognitive Spend Intelligence platform that harmonizes and enriches procurement data from various sources, creating a unified view of spend. The platform uses AI-powered data cleansing and classification to improve data quality and accuracy, with human review built in. On top of this governed data layer, Opportunity Agents scan spend, supplier, and contract data to surface savings opportunities ranked by value and confidence, including tail spend, maverick spend, price leakage, and purchase price variance. The Atlas copilot enables users to ask questions, generate charts and reports, and draft category strategies grounded in their data. Every finding includes evidence, confidence scores, and suggested actions, and can be assigned to initiatives with tracked savings.
Target Audience
Primary users are procurement category managers and procurement teams seeking to improve data quality, identify cost savings, and optimize supplier relationships, as well as CPOs needing executive visibility into savings pipelines.
Features
- Six specialist Opportunity Agents: Tail Spend, Maverick Spend, External Benchmark, PPV, Price Leakage, and Master Agreement, each targeting a specific savings category
- Data Foundation Agents that auto-categorize every spend line to the user's taxonomy, normalize duplicate suppliers into a single master, and enrich data with risk, price index, market intelligence, and ESG signals
- Confidence scores and disclosed methodology on every savings estimate, with auditable evidence trails for all findings
- Atlas copilot for ad-hoc spend queries, board-ready report generation, and data-grounded category strategy drafting
- Human-in-the-loop workflow: findings require team review before action, with no auto-execution
- Dashboard tracking identified versus realized value, with CPO-level visibility into savings pipeline progress