How we work.
Four operating principles that make the difference between a slide deck and a working system in production.
Forward-deployed engineers
We don't send consultants with slide decks. We embed engineers directly inside your team — working in your Slack, your codebase, your infrastructure, alongside your people day-to-day.
They attend your standups. They understand your constraints. They build capability in your team continuously as the project progresses — so when they exit, your engineers can operate and extend what was built without ongoing dependency.
- →Works inside your team, not from a remote office
- →Builds capability in your engineers as the project runs
- →Exits cleanly with full documentation and runbooks
- →No lock-in — you own every line of code we write
“The best way to transfer knowledge is to build together.”
Token cost · Same workload
Indicative comparison of published API pricing against self-hosted open-source inference. Actual costs vary by workload, model and infrastructure.
Open-source cost architecture
Enterprise AI doesn't have to mean hyperscaler pricing. We select and run production-grade open-source models on hardware you control.
Published API pricing for the major hosted models runs roughly 5–10× above the cost of self-hosted open-source inference on comparable workloads. What you actually save depends on your workload, model choice and infrastructure, and we model it with you before you commit. What is certain is the shape of the cost: fixed infrastructure rather than a per-token bill that grows with adoption.
Privacy-first deployment
On-premise is our default architecture, not a premium add-on. Every system we build is designed so that your data never leaves your infrastructure — no shared model weights, no cloud logging, no third-party API calls during operation.
This matters for regulated industries, Australian Privacy Act compliance, and any organisation with operationally sensitive data. Where cloud models are used (rare), we implement data masking by default before any external call.
- →Data never leaves your infrastructure
- →No shared model weights or training on your data
- →Australian Privacy Act and data sovereignty compliant
- →Designed for regulated environments, including health and financial services
Design commitments
- →No cloud API calls during operation
- →On-premise deployment by default
- →No shared model weights, and no training on your data
- →Designed for Australian Privacy Act compliance
Specialised agents from briefs
For Full Transformation engagements, we leave behind a meta-system that builds and tunes specialised AI agents from operational briefs — without requiring code changes from your team.
The aim is that your team can stand up a new agent for a fresh operational need in days, not weeks. Agents learn from operator feedback loops and improve over time. When we exit, your team has the tooling, not just the agents.
- →Build new agents from a plain-language brief
- →Agents learn from operator feedback and corrections
- →No code changes required for new agent types
- →The tooling itself is the handover artifact
Brief
Spec
Live agent
Brief → spec → live agent
Ready to see what AI can do inside your business?
Start with a two-week Discovery Sprint. Fixed price. No lock-in. Walk away with a clear roadmap — or a working prototype.
Email KK.Santhanam@cxomirror.com