FairCloud AI provides AI‑powered cloud optimization that continuously analyzes usage and automatically scales resources to match application demand, eliminating over‑provisioning without impacting performance. The platform integrates with AWS to deliver real‑time predictive scaling and custom cost‑saving plans, helping businesses reduce cloud spend by up to 57% while also lowering their carbon footprint. It offers live monitoring and smart scheduling to keep infrastructure efficient and cost‑effective.
Funding
Funding not disclosed
Founders
Product
Problem
Many organizations allocate excess cloud resources because manual capacity planning is imprecise, leading to consistent overspend of 30% + and increased operational complexity. The lack of real‑time, automated optimization forces teams to balance cost against performance, often resulting in either overprovisioned infrastructure or service degradation.
Solution
FairCloud AI delivers an AI‑driven optimization platform that continuously analyzes AWS workloads and automatically adjusts compute, storage, and serverless resources to match actual demand. Machine‑learning forecasts predict usage spikes, enabling predictive scaling without manual intervention. The system operates with zero performance impact and requires no changes to existing infrastructure, achieving typical cost reductions of around 57%. Deployment is completed within 24–48 hours, after which live monitoring and custom cost‑saving recommendations keep savings ongoing. Clients are charged only a percentage of the verified savings, aligning incentives with cost efficiency.
Target Audience
Primary customers are startups, small‑to‑medium businesses, and enterprise IT teams that run workloads on AWS and seek to lower cloud spend while maintaining performance.
Features
- Machine‑learning models that predict workload demand and auto‑scale EC2, RDS, and Lambda resources in real time
- Seamless AWS integration with no code changes or infrastructure rewrites
- Continuous live monitoring dashboard that visualizes usage, savings, and performance metrics
- Smart scheduling engine that consolidates idle instances and rightsizes resources based on historical patterns
- Instant implementation workflow delivering optimization within 24–48 hours
- Zero‑disruption operation ensuring no service interruptions during scaling actions
- Transparent, performance‑based pricing (5% of realized savings) with no upfront fees or long‑term contracts
- Reduced carbon footprint through lower resource consumption