As enterprises accelerate AI adoption, 85% of AI projects fail due to accuracy and reliability challenges. Existing AI tools lack granular evaluations, structured feedback loops, and data-driven improvement strategies, making AI development inconsistent and error-prone.
To address this, Future AGI has secured a $1.6M pre-seed funding round to scale its AI lifecycle management platform, enabling businesses to build and maintain high-performing AI applications with unparalleled accuracy. The round was co-led by Powerhouse Ventures and Snow Leopard Ventures, with participation from Angellist Quant Fund, Swadharma Source Ventures, Saka Ventures, and 30+ AI industry leaders.
Bridging the AI Accuracy & Reliability Gap
Current AI tools fail in:
Granular error analysis for pinpointing failures
Generating high-quality synthetic data
Automating feedback and optimization loops
Ensuring cross-functional collaboration
Most AI evaluations remain manual and inconsistent, often relying on guesswork rather than data-driven experimentation. This fragmented approach slows down development and prevents AI from being as rigorous as modern software engineering.
Future AGI’s Breakthrough AI Lifecycle Management Platform
Future AGI’s platform enables enterprises to:
Rapidly iterate AI models, prompts, and data
Conduct deep multi-modal evaluations across text, images, and agents
Leverage real-time observability and auto-optimization
Reduce AI product development time by up to 95%
“AI is becoming the new software, but its widespread adoption faces a critical challenge—reliability at scale,” said Nikhil Pareek, CEO of Future AGI. “We’re building the foundational layer that ensures AI systems are trustworthy, automating the evaluation, monitoring, and improvement of AI performance.”
Real-World Impact: AI Optimization at Scale
A Series E sales-tech company used Future AGI’s LLM Experimentation Hub to achieve 99% accuracy in its AI pipeline, accelerating processes 10x faster.
An AI image generation company reduced evaluation costs by 90%, maintaining 99% accuracy while minimizing human intervention.
Future AGI’s platform also supports AI in robotics and autonomous vehicles, simulating edge cases for improved AI safety before deployment.
Founders & Team Expertise
Founded by Nikhil Pareek and Charu Gupta, Future AGI was born out of their frustration with AI model failures, data inconsistencies, and inefficiencies.
- Nikhil Pareek: Former AI founder, holds multiple patents, built autonomous drones, and tackled complex Fortune 50 AI challenges.
- Charu Gupta: A revenue growth veteran who has scaled multiple startups to $100M+ in revenue.
Backed by 30 AI researchers and ML engineers from Microsoft, Amazon, and Ivy League institutions, the team is redefining AI accuracy and trust at scale.
Investor Confidence in Future AGI
“The biggest challenge enterprises face today is ensuring AI accuracy and reliability,” said Sri Peddu, General Partner at Powerhouse Ventures. “Future AGI’s AI lifecycle management platform is uniquely positioned to solve this problem at scale.”
Abraham Othman, PhD, from Angellist Quant Fund, added: “Future AGI is attracting top-tier talent, which is a testament to its potential to redefine AI development.”
What’s Next for Future AGI?
With its Bay Area headquarters and R&D center in Bangalore, Future AGI plans to:
Accelerate product development
Expand engineering and growth teams
Enhance its proprietary AI technology stack
As AI expands into multimodal applications (text, images, video, and robotics), Future AGI is positioned to be a cornerstone in building reliable, high-performance AI systems for the future.
