01
Discover
Map the work and its owner.
Start with the maintenance workflow, users, sources, permissions and business constraints.
How we deploy
From workload to operated private AI.
The sequence matters: understand the work, prove the model and capacity, then build the environment that can be supported.
Inside the workflow / Illustrative example
From a workload to an operated system.
Eight implementation stages produce a private AI environment with evaluated workflows and an accountable operator.
Discover
Map the work and its owner.
Start with the maintenance workflow, users, sources, permissions and business constraints.
02
Benchmark
Test before sizing.
Compare candidate models against approved examples and evaluate quality, latency and concurrency.
03
Architect
Design the whole system.
Specify compute, Company Brain, agent harness, interfaces and operating controls together.
04
Deploy
Install the private foundation.
Configure model serving, the gateway, identity, monitoring and backup. Hardware is normally purchased by the customer.
05
Connect
Link the existing stack.
Create approved knowledge ingestion and bounded interfaces to the systems the team already uses.
06
Harness
Define the agent’s operating rules.
Build the instructions, tools, memory, approvals and evaluation paths for the agreed work.
07
Validate
Prove the acceptance boundary.
Test retrieval, permissions, tool actions, failure cases, latency and recovery before handoff.
08
Operate
Keep the system accountable.
Assign operating ownership for monitoring, patching, model evaluation, connector maintenance and recovery.
What we engineer
The details that make this workflow dependable.
Discover
Map the workflow, users, systems, data, permissions, business owner, and constraints.
Benchmark
Evaluate candidate models and infrastructure against customer-specific workload examples.
Architect
Design compute, storage, networking, Company Brain, harness, integrations, identity, and controls.
Deploy and connect
Install model serving, gateways, observability, backups, and approved system interfaces.
Harness and validate
Build tools, memory, routing, safeguards, approvals, and acceptance tests for quality, permissions, actions, latency, recovery, and failure cases.
Operate
Monitor, patch, evaluate, update models, maintain connectors, review incidents, and expand from evidence.
Start with proof
Bring us the workflow you want to improve.
We map the work, test model and capacity requirements, design the controls, and define a practical implementation.