Train agentic networks on your knowledge.
Turn buried enterprise knowledge into autonomous execution. We train coordinated networks of Small Language Models on your data, inside your walls, never the reverse.
From raw knowledge to a working agentic network.
- 01
Ingest your knowledge
Connect your documents, systems and processes. Eigen Networks builds a sovereign, localized knowledge base inside your infrastructure.
- 02
Decompose the objective
Hierarchical Task Networks break high level goals into structured, executable plans, with no fragile prompt chains.
- 03
Match & tune the models
Right sized SLMs are selected and adapted to your domain, so each task runs on the most efficient model that meets the bar.
- 04
Coordinate the agents
Agents collaborate, adapt, and escalate to humans when it matters, improving as your knowledge base compounds.
Frequently asked questions
What does agentic network training involve?+
We ingest your enterprise knowledge into a localized knowledge base, decompose your objectives into Hierarchical Task Networks, and match and tune right sized Small Language Models to each task, all within your own infrastructure.
Does our data leave our environment during training?+
No. Training and adaptation happen inside your perimeter. No proprietary data is sent to external APIs or used to train anyone else's models.
How is this different from fine tuning one large model?+
Rather than fine tuning a single large model, we train a coordinated network of smaller, specialized models. This is more economical, easier to run privately, and more adaptable as your needs change.
How does the system improve over time?+
Agents build a living institutional knowledge base from your data, so the network's intelligence compounds, with accuracy and coverage improving as more of your knowledge is connected.