Your terminology, systems and processes shape the AI we build. Origon fine-tunes models, connects business data and develops agents and applications around the work.
Because we build the underlying platform, our engineers can address the system as a whole—and continue developing it after launch.
Agents can follow up on missing information, respond to events and return to unfinished tasks. Origon’s orchestration keeps track of the work.
The runtime coordinates workers, schedules tasks and handles retries and interruptions.
Retrieval and memory bring relevant information, earlier decisions and commitments into an agent’s next step.
Our engineers connect the sources and tools behind that step, using 100+ pre-built connectors or custom REST, GraphQL, webhook and MCP integrations.
We fine-tune models on enterprise data to reflect your terminology, processes and domain knowledge. Foundation models and your own models are also supported.
On Origon Cloud, training runs on our GPU clusters and models are served by our inference engine. Evaluation measures quality, performance and cost for the workload.
Our engineers build the interface alongside the agents, model instructions and integrations behind it.
People can receive results, approve decisions and take over work in Origon applications, existing software or a custom interface.
Our work can extend to GPU infrastructure and private deployment when the business requires it.
Models, components and connections are selected for the environment where the system will run.
New processes, changing data and software updates all affect an AI system. Our engineers maintain integrations and tune models and agents as part of the ongoing engagement.
Execution records and evaluations show where attention is needed, connecting each change to the work it should improve.