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§ Private Profile · San Francisco, CA, USA
Thoras.ai is a technology company.
Thoras.ai provides an AI-driven platform for predictive Kubernetes autoscaling, optimizing cloud infrastructure. Its product uses adaptive AI to anticipate workload demand, ensuring precise scaling. This proactive management maintains stable performance, eliminates over-provisioning waste, and prevents under-provisioning issues, driving enhanced efficiency and significant cost savings in cloud environments.
Thoras.ai was co-founded by twin sisters Nilo Rahmani and Jennifer Rahmani from tech careers. Their insight stemmed from the difficulty of achieving system reliability without excessive cloud spending. They aimed to build an intelligent solution, dynamically balancing performance and resource efficiency, thereby redefining infrastructure optimization.
Organizations using Kubernetes leverage Thoras.ai for improved system reliability and optimized cloud spending. The company envisions empowering engineering teams with seamless workload efficiency, transforming how infrastructure responds to dynamic demand. Thoras.ai seeks to establish a new benchmark for adaptive infrastructure management, fostering operational excellence and optimal resource allocation.
Thoras.ai has raised $7.0M across 2 funding rounds.
Thoras.ai has raised $7.0M in total across 2 funding rounds.
Thoras.ai has raised $7.0M across 2 funding rounds. Most recently, it raised $5.0M Seed in January 2025.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Jan 1, 2025 | $5M Seed | VAN Jones | Darling Ventures | Announced |
| Mar 1, 2024 | $2M Seed | Focal VC, Storytime Capital | Chemistry VC, Comal Ventures, Darling Ventures, Northside Ventures, Y Combinator, Balaji Srinivasan, Derrick LI | Announced |
Thoras.ai has raised $7.0M in total across 2 funding rounds.
Thoras.ai's investors include Van Jones, Darling Ventures, Focal VC, Storytime Capital, Chemistry VC, Comal Ventures, Northside Ventures, Y Combinator, Balaji Srinivasan, Derrick Li.
Thoras.ai is a Washington, D.C.-based technology company that builds an AI-driven platform for predictive autoscaling and anomaly detection in Kubernetes and cloud workloads.[1][2][3] It serves SRE and DevOps teams at enterprises and Series A startups in sectors like ecommerce, edtech, and private data centers, solving the problem of reactive infrastructure management that leads to downtime, overprovisioning, and cloud costs ballooning up to 60% higher than necessary.[2][3][7] By ingesting time-series metrics from tools like Prometheus, Datadog, and Splunk, Thoras predicts demand fluctuations—factoring in real-world events like product launches or traffic spikes—and autonomously scales resources proactively, reducing costs by up to 60% and resolving issues 70% faster while boosting uptime.[1][2][3]
Launched with $1.5 million in seed funding in March 2024, Thoras demonstrates strong early growth through customer pilots and a focus on container-based environments, positioning it to capitalize on exploding cloud spend pressures amid AI infrastructure demands.[1][7]
Thoras.ai was co-founded by twin sisters Nilo Rahmani (CEO) and Jennifer (Jen) Rahmani (COO), who left established tech careers to tackle cloud reliability challenges they encountered firsthand.[1][2][5][7] Nilo brings software engineering experience from Slack and Goldman Sachs, while Jen spent a decade as a DevOps engineer on the DoD's largest AI surveillance program, architecting resilient cloud infrastructure and large-scale monitoring systems.[1][5]
The idea emerged from their realization that intuition alone fails for scaling critical, costly cloud services—especially as businesses grow and cloud expenses cripple operations.[1][2] They bootstrapped with synthetic data before pivoting to customer-led development, targeting Series A startups after finding enterprises too risk-averse for early experiments.[7] A pivotal moment came with their $1.5 million raise in March 2024, enabling platform acceleration for container environments and real customer integrations.[1]
Thoras.ai stands out in the crowded cloud observability market (e.g., New Relic, Splunk, Dynatrace) through these key strengths:
Thoras.ai rides the cloud cost crisis trend, where enterprises face exponential bills from AI workloads, unpredictable traffic, and post-pandemic growth, shifting from "reliability at all costs" to efficiency without sacrificing uptime.[2][3] Timing is ideal amid 2024-2025 observability expansions (e.g., SUSE's AI tools) and Kubernetes maturity, where even advanced teams waste time on reactive firefighting during events like Black Friday.[2][3][5]
Market forces like surging cloud spend (projected to hit trillions) and AI's demand for precise resource allocation favor Thoras, which influences the ecosystem by enabling leaner SRE teams and self-optimizing infra—potentially accelerating startup scaling in AI-native eras.[1][2][6]
Thoras.ai is primed to expand from pilots to broader adoption, targeting Kubernetes-heavy enterprises with predictive scaling as cloud budgets tighten further in 2026.[7] Trends like multi-modal AI inference and edge-hybrid clouds will amplify demand for its non-LLM, ROI-focused models, potentially evolving it into a full infra-automation suite.[2][3][5]
As the Rahmani sisters scale their "twin effect" vision, Thoras could redefine SRE as proactive artistry, supercharging cloud optimization just as their $1.5M seed ignited—delivering reliability without the waste that still plagues the industry.[1][7]