Engineered Intelligence Systems

ML infrastructure, built to specification.

We design and deploy machine learning systems for organizations with hard technical problems and no appetite for guesswork. Custom pipelines, dedicated compute, measurable outcomes — delivered as a service so you don't have to build the team.

What We Build

Data Pipeline Architecture

We build ingestion systems that take unstructured inputs — documents, images, feeds, archives — and produce structured, queryable intelligence at scale.

Large-Scale Inference

Production inference infrastructure sized to your workload. Low-latency serving, batch processing across GPU clusters, and optimization for cost-per-query at volume.

Custom Model Development

Task-specific models trained, fine-tuned, and validated against your data. Not off-the-shelf wrappers — purpose-built systems that solve the actual problem.

Automated Intelligence Systems

End-to-end automation that connects extraction, analysis, and delivery into a single operational loop. Systems that run unattended and surface what matters.

How we work

We scope precisely, build in weeks not quarters, and hand over systems — not slide decks. Every engagement starts with a hard technical assessment and ends with infrastructure you own.

Precision

Every engagement begins with a rigorous scoping process. We define what "done" looks like before we write a line of code.

Velocity

Small teams, deep expertise, minimal overhead. We ship production systems on timelines that would surprise you.

Ownership

You get the system, the documentation, and the knowledge transfer. We build to hand off, not to create dependency.

PyTorchCUDATransformer ArchitecturesGPU Cluster OrchestrationONNX RuntimeDistributed TrainingReal-Time InferenceVector DatabasesKubernetesTensorRTPyTorchCUDATransformer ArchitecturesGPU Cluster OrchestrationONNX RuntimeDistributed TrainingReal-Time InferenceVector DatabasesKubernetesTensorRT

50,000+

GPU-hours deployed

<100ms

inference latency

1M+

documents processed