Avastha is reinventing AI pricing by replacing unpredictable token-based billing with outcome-based payment models. The company enables businesses to pay for AI work based on completed deliverables and acceptance criteria, rather than per-token usage. This approach aligns costs with actual results, making AI spending more predictable and reliable.
- Artificial Intelligence
- Software Only
Funding
Funding not disclosed
Founders
Product
Problem
Current AI pricing relies on token-based billing, where every prompt is charged in full regardless of whether the output meets the user's requirements. This creates unpredictable costs and misaligned incentives, as businesses pay for failed attempts and incomplete work. The "token lottery" model forces users to absorb the financial risk of unreliable AI outputs.
Solution
Avastha is reinventing the economics of AI by shifting from metered token consumption to outcome-based pricing. The platform enables businesses to define work orders with specific acceptance criteria and pay only when those criteria are met. This approach mirrors traditional professional service arrangements like fixed quotes or conditional payments, making AI spending predictable and tied to actual delivered value. By aligning payment with results, Avastha reduces financial waste and encourages AI systems to focus on completing tasks correctly rather than generating token volume.
Target Audience
Primary customers are businesses and developers who rely on AI for production work and need predictable, results-based pricing instead of unpredictable token consumption costs.
Features
- Outcome-based pricing model where payment is tied to completed acceptance criteria rather than token usage
- Work order system that lets users define specific deliverables and quality standards before engaging AI
- Budget tracking with transparent invoicing that shows costs only when tasks are successfully completed
- Spec sheet functionality for formalizing task requirements, including test criteria and quality checks
- Alternative to traditional token billing that eliminates the "house odds" dynamic of paying for failed attempts