Fission Labs

Fission Labs was founded in 2008 by three engineers in India and has grown to over 150 team members. The company specializes in applied AI and ML engineering, generative AI systems, and cloud infrastructure—with a particular focus on building production-ready solutions rather than prototypes. They've delivered over 1,500 solutions for 100+ global clients, many of whom have gone on to raise funding or been acquired by Fortune 1000 companies. Leadership includes Eswar Lingam (CEO, 20+ years in digital transformation), Kishore Poreddy (20+ years in technology), and Dr. Hemant Joshi (CTO of Generative AI Practice, 20+ years in AI/ML with previous roles at Acxiom, Dataminr, and Tumblr). The company is AWS Certified Advanced Consulting Partner and holds AWS Generative AI Software Competency Partner status. They're also Great Place to Work Certified.

Services and capabilities

Fission Labs organizes its offerings into three main buckets: foundational AI/ML, generative AI, and model operations with infrastructure.

For foundational work, they provide data science and analytics (exploratory analysis, statistical modeling, A/B testing, business intelligence), machine learning solutions (predictive analytics, classification, time series forecasting, customer segmentation, anomaly detection), and deep learning services (computer vision, NLP, speech recognition, transfer learning).

On the generative AI side, they build retrieval-augmented generation (RAG) systems for enterprise knowledge bases and document Q&A; custom LLM fine-tuning and prompt engineering; and specialized applications like chemical data extraction, scientific literature mining, and automated report generation. A key offering is FloTorch, their proprietary enterprise AI gateway built in partnership with AWS. FloTorch handles agentic workflow orchestration, inference routing, vector database management, and includes built-in observability and tracing. Clients use it to optimize for cost, latency, and throughput without changing existing workflows.

They also handle model operations: architecture design, hyperparameter tuning, MLOps pipeline development, containerized deployment, real-time inference systems, performance benchmarking, and latency/cost optimization. Cloud infrastructure spans AWS, Azure, GCP, and Oracle.

Beyond AI, Fission Labs offers data engineering (scalable pipelines and analytics platforms), cloud consulting (modernization and security), web and mobile app development, quality assurance, Salesforce consulting, and ServiceNow solutions.

Notable work

A fashion retail company built an AI-driven platform using AWS SageMaker for virtual try-ons (Stable Diffusion), Amazon Rekognition for body measurements, and Amazon Personalize with Bedrock for styling recommendations. The result: return rates dropped by up to 60%, conversions increased 90%.

A professional services firm implemented a RAG-based knowledge platform on FloTorch, unifying 23 regulatory sources via S3 and Elasticsearch. They achieved 75% reduction in research time, saving over $3,750 daily, and hit 90% adoption in three months.

An HR technology company deployed an AI-powered HRMS and labor analysis platform on AWS with fine-tuned LLM models. One client reported a 65% improvement in labor market prediction accuracy, over 30% reduction in operational costs, and expansion into 8+ new markets.

Other named clients include BrightReturn (law firm workflow AI), SaaS Growth Dispatch (AI newsletter POC), Astound, and earlier-stage work with Peel (a video content discovery platform that reached 130M+ users).

How they work

Fission Labs follows agile scrum with sprint-based delivery. They offer three engagement models: fixed-price (for clear requirements and small projects/MVPs), time & material (for dynamic requirements and long-term engagements), and milestone-based (for complex scope with rigid requirements). Their implementation methodology is "Think Big, Start Small, Scale Fast": a 3-day digital workshop for discovery and architecture design, rapid prototyping and MVP development, then productionization with multi-tenant infrastructure, system integration, continuous monitoring, and L2/L3 support. They assemble custom agile pods combining UX/UI designers, developers, DevOps engineers, QA engineers, product managers, data engineers, business analysts, and scrum masters. A Centre of Excellence layer provides solution architects, domain experts, best practices, research, training, and knowledge transfer to reduce operational cost and boost ROI.