BrainRivetAI agents
Purpose-built agents that work with your data, use approved tools, and carry out defined tasks with clear permissions and escalation paths.
Capabilities
AI systems that can understand, coordinate, and act.
We build the agent, the workflow around it, and the platform your teams need to operate it. Each capability is designed around a defined business task.
Agentic workflows
Coordinate agents, people, and business systems across long-running work, with checkpoints, retries, and an accountable owner for every exception.
Knowledge & document intelligence
Make approved knowledge usable through retrieval, document extraction, grounded answers, and traceable sources.
AI-native platforms
Build the applications, integrations, and operating layers that turn individual AI capabilities into a connected business platform.
Model evaluation & adaptation
Choose models against your tasks, evaluate material errors, and improve prompts, retrieval, or fine-tuning using reviewed examples.
AI operations & governance
Monitor quality, latency, cost, and tool use. Version model behaviour and maintain the controls needed for release, review, and recovery.
The operating layer matters.
Reliable agentic work depends on the software around the model.
Integration & orchestration
Approved APIs and tools connect agents to business systems. Durable workflows maintain state, handle retries, and make incomplete work visible.
Evidence & evaluation
Task-specific evaluation checks whether outputs are grounded and actions are correct. Review records preserve the context behind consequential decisions.
Permissions & control
Agents receive scoped access. Human approval gates, audit trails, and release controls follow the risk and responsibility of the task.
Choose the model for the task.
We assess hosted and open-weight models against quality, data handling, latency, cost, and operational requirements. Retrieval brings approved knowledge into the workflow; fine-tuning is considered when measured gaps justify it.
A multi-agent design earns its complexity when distinct responsibilities or permissions make coordination useful. Simpler tasks can use a single agent or a deterministic workflow.
Where could AI take responsibility?
Bring us a workflow, a platform idea, or an operational challenge.