We optimized the compute layer for the next generation of data and AI workloads. Jobs run faster with less infrastructure. No changes to your existing data lake.
It’s as simple as that.
A plug-and-play platform for data and AI jobs at scale. Up to 25× faster, on up to 95% less infrastructure.
Every claim we make is anchored to a customer benchmark. Across financial services, defense, healthcare, and logistics — same pattern.
Falcon runs within your existing data ecosystem. Bring compute workloads over to run on our engine.
Achieved in production with Haevek replacing Apache Spark on PDF → OCR → LLM pipelines with standardized infrastructure.
“Substantial gains in performance and scalability while reducing overhead”
Sushil Muzumdar, Everlign Co-founder
Falcon for data analytics:Extracts, transforms, and analyzes data 80% faster and at 94% lower cloud costs.
Falcon for logistics companies:Distributes frames across compute clusters, resulting in 2.5x faster image embeddings than native PyTorch.
Falcon for healthcare applications:Lists and partitions PDFs for parallel work, resulting in 75% quicker processing and 80% lower infra costs.
Bring up to three pipelines. We benchmark Falcon head-to-head against your current setup, train your team, and deliver a quantified value assessment in 2–4 weeks.
Up to 3 pipelines, on your data, in your environment
Apples-to-apples benchmarks against your current stack
No replatforming. No commitment.