Go ask Alys

The AI/ML partner that understands your data

Deploy production-ready machine learning pipelines and intelligent agents powered by graph-based knowledge systems. Alys handles the complexity so you can focus on the decisions that matter.

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Intelligence at Scale

Alys is the AI/ML partner for teams who demand more from their data

Built for data scientists, ML engineers, and product teams who need production-ready infrastructure without the operational overhead. Alys provides the complete MLOps stack from training to serving, with distributed AI orchestration built in.

Whether you're building intelligent chatbots, document analysis systems, or multi-agent collaborative platforms, Alys helps you deploy faster and scale smarter.

Built for Production

What every engagement delivers to deploy intelligent systems

MLOps That Scales

Automated training, versioning, and deployment pipelines that take models from notebook to production in minutes, not months.

Distributed AI/OS

Orchestrate multiple AI agents seamlessly with built-in coordination, resource management, and fault tolerance.

Graph-Based Intelligence

Move beyond vector search. Knowledge graphs that understand relationships and context, delivering RAG systems that actually comprehend your domain.

Agentic Analytics

Semantic layers and lineage built for decision fitness, not just dashboards. We test every agentic workflow against real data before it reaches production.

Hybrid Model Routing

Route between local models and frontier APIs by policy. Cost, latency, and data sensitivity decide where inference runs — not guesswork.

Enterprise Harness

Evaluate, govern, observe. Monitoring, logging, audit trails, and release controls built in from day one, not bolted on after launch.

How We Work

The same three-phase playbook on every engagement, start to finish

Discover

Audit your data, models, and use cases. We test the claims before we plan around them.

Engineer

Stand up the pipelines, knowledge graphs, and agents — hands-on, iterative, in your environment.

Launch

Ship to production with monitoring, evaluation, and audit trails already wired in.

Transparent by Design

You see the reasoning, not just the results

Every architecture decision, benchmark, and model we ship comes with the reasoning behind it — including the approaches that didn't pan out. We document dead ends the same as wins, tested hands-on and laid out for your team to inspect, not buried in a vendor deck.

Hands-on testing
Explainable by default
Setbacks shared openly

Modern Infrastructure

We build on cutting-edge technology for maximum performance

Python ML Pipelines

Native support for scikit-learn, PyTorch, TensorFlow, and popular ML frameworks

Kubernetes-Native

Scalable deployment on any cloud or on-premises infrastructure

Graph Databases

Relationship-aware knowledge representation with Neo4j and compatible systems

LLM Integration

Seamless integration with OpenAI, Anthropic, and custom model endpoints

Real-Time Inference

Low-latency model serving with automatic scaling and load balancing

Observability

Built-in monitoring, logging, and tracing for full system visibility

Let's Build Something Intelligent

Ready to put your data to work? Then go ask Alys