Finte

The startup operates a fintech platform that extracts contextual data from contracts and invoices using advanced data processing techniques. This enables cloud-based companies to optimize financial decision-making and improve cost forecasting.

Boulder, United States

Updated 2 months ago

Funding

$3.1M 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.

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Cloud-based companies often struggle with unpredictable infrastructure costs and a lack of visibility into the financial implications of engineering decisions. Finance teams need better spend predictability and contribution margins, while engineering teams require data-driven tools to make cost-conscious design choices. Existing tools often fail to provide a comprehensive view of cloud, data, monitoring, managed services, and AI/LLM spend, hindering effective collaboration and accurate forecasting.

Solution

FinTe is a FinOps platform that provides cloud-based companies with enhanced visibility and control over their infrastructure spending. By extracting contextual data from contracts and invoices, FinTe builds a comprehensive view of cost of goods sold (COGS). The platform facilitates collaboration between finance and engineering teams, enabling strategic conversations and more accurate forecasting. FinTe offers opinionated recommendations that help engineering teams catch costly issues early in the development process, while providing finance teams with the spend predictability they need. By deep-diving into major spend categories like cloud, data, monitoring, managed services, and AI/LLMs, FinTe delivers a complete picture of the economics of the business.

Target Audience

FinTe primarily targets finance and engineering teams at cloud-based companies, particularly growth-stage SaaS companies, who need better visibility into infrastructure spend and improved collaboration for efficient growth.

Features

Extraction of contextual data from contracts and invoices to build a comprehensive view of COGS
Cost modeling for AI/LLM spend, turning AI features from cost centers to profit generators
Spend tracking and optimization across major categories: cloud, data, monitoring, managed services, and AI/LLMs
Opinionated recommendations for engineering teams to make cost-conscious design decisions
Shared pane for finance and engineering teams to have strategic conversations and build more accurate forecasts
Identification of underutilized reserved cloud instances to align spend with product revenue
Total Cost of Ownership (TCO) analysis for data infrastructure