The Product
Falcon is a compiled, Kubernetes-native distributed compute engine.
It replaces legacy systems like Spark, Databricks, EMR, and custom solutions — without changing your storage, your catalog, or your governance layer. Deployed in your environment. Priced for efficiency.
Capabilities
Batch ETL, streaming, AI inference, content extraction, analytics, low-latency serving — handled by one runtime, configured through one tool, deployed wherever you need it.
Falcon optimized pipelines compile down to vectorized native code. Same data. Same outputs. Different engine.
A F100 Systems Integrator tested Falcon on a Spark ETL + ONNX inference pipeline with no code changes.
Helm-installed to your K8s cluster. No JVM, no fixed driver footprint, no just-in-time compilation, no bloat.
A commercial aggregator replaced their Databricks Photon clusters for real-time ETL. Same latency. 93% less infrastructure.
PDF → Tesseract OCR → LLM metadata extraction. Single Falcon pipeline, configured in minutes. Optimal CPU/GPU impedance matching.
xTech AI Grand Challenge finalist. Adversarial detection + classification on millions of images with 16 cores + 4 GPUs.
FMV processing at 30 fps. Object detection in 80 ms, OCR in 80 ms, embeddings in 43 ms — 2.5x faster than native PyTorch.
No external dependencies beyond Kubernetes. No phone-home. End-to-end encryption, mTLS, OIDC, full audit logging.
Architecture
Falcon sits between the systems that produce data and the systems that consume it — a single, compiled engine for batch, streaming, and inference. The lakehouse, catalog, and infrastructure underneath stay yours.
Object stores, relational tables, text, images, video, streams, events. Falcon ingests directly — no staging tier required.
Control plane for operators, transparent orchestration for efficient resource usage, and a hyper-optimized job execution engine for the work itself. All compiled, all native.
Applications, dashboards, agents, BI, APIs, alerts, and the systems of record that drive your enterprise.
Delta Lake, Iceberg, Hudi, Snowflake, Postgres, Oracle, Elastic, Mongo, S3. Cloud, on-prem, edge — infinitely pluggable.
Deployment
Helm-installed into your namespace. OIDC for auth. RBAC for access. IAM for storage. No external network paths required. Up and running in minutes.
EKS, AKS, GKE — your existing managed Kubernetes, your existing cloud account, your existing IAM.
OpenShift, Rancher, vanilla K8s. Bring your own hardware; we run inside your firewall.
Zero external dependencies. Image registries you control. Suitable for FedRAMP, IL4+ and classified work.
MicroK8s or k3s on a single-core sensor pod. Same binary as the cloud. Identical operating model.
vs. Legacy Compute
The differences aren't configuration tweaks. They're architectural. Spark and its derivatives carry overhead that Falcon was designed to eliminate.
| SPARK · DATABRICKS · EMR · Others | FALCON | |
|---|---|---|
| Runtime | JVM, interpreted, abstracted | Rust, compiled to native code |
| Memory | Garbage-collected, GC pauses | Direct memory control, no GC |
| Determinism | Non-deterministic (JIT-optimized) | Deterministic compilation |
| Concurrency safety | Not guaranteed | Guaranteed by compiler |
| Hardware abstraction | Hypervisor + container + JVM | Hypervisor + container |
| Cluster posture | Always-on, fixed driver footprint | Scale-to-zero by default |
| Edge / air-gap | Cloud-only or limited | Cloud, on-prem, air-gap, single-core |
| Security posture | Shared-responsibility, varies | Secure-by-Design · mTLS · Hardened containers · Zero Trust |
Deployment
Helm-installed into your namespace. OIDC for auth. RBAC for access. IAM for storage. No external network paths required. Up and running in minutes.
EKS, AKS, GKE — your existing managed Kubernetes, your existing cloud account, your existing IAM.
OpenShift, Rancher, vanilla K8s. Bring your own hardware; we run inside your firewall.
Zero external dependencies. Image registries you control. Suitable for FedRAMP, IL4+ and classified work.
MicroK8s or k3s on a single-core sensor pod. Same binary as the cloud. Identical operating model.
Security
Our team built and operated Top Secret and Special Access programs. Falcon was designed under these constraints from day one.
0 Crit/High/Med CVEs at release. Memory safety enforced at compile time. Concurrency safety guaranteed by the orchestration layer.
End-to-end encryption. mTLS service-to-service. OIDC/SSO for users. RBAC for resources. Full audit logging.
We never see your data. Falcon runs in your cluster, reads from your storage, writes to your storage. No egress, no externally-managed service.
Pricing
Tiered annual subscriptions, from starter to enterprise. You pay for capacity, not utilization — the more you use, the more you save.
| TIER | MAX CONCURRENT CORES | POSITIONING |
|---|---|---|
| Tier 1 | 64 | Pilot or single workload — proves out a batch or streaming job in production. |
| Tier 3 | 256 | Most common land — a team or business unit consolidating several workloads onto Falcon. |
| Tier 5 | 1,024 | Production at scale — multiple teams, mixed batch + streaming + inference, mission-critical SLAs. |
| Tier 7 | 4,096 | Enterprise-wide — Falcon as the standard compute layer across the org, replacing legacy Spark estate. |
| Tier 9 | Custom | Negotiated — global rollouts, regulated industries, sovereign / air-gapped deployments. |
Test Flight
Free. 2-4 weeks. Apples-to-apples results on your real workloads. No replatforming. No commitment.