How We Work
Successful AI adoption is rarely about the model itself—it is about definitive system boundaries, data integrity, and deterministic failure controls. Every implementation at Caliper is engineered around four non-negotiable architectural principles:
What may the system execute autonomously, and what requires sign-off?
We build strictly according to Gated Autonomy. AI models fetch context, transcribe acoustic records, parse unstructured communications, and draft operational proposals. But an authorized human specialist always reviews and authorizes the final external dispatch or binding decision. The system never commits commercial transactions independently.
Where does your data reside, and who can inspect it?
EU/EEA is our standard for where your data resides, and we work within GDPR. If you choose a supplier outside the EU, for example in the US, that is your informed decision, based on a transfer impact assessment (TIA). We use closed enterprise agreements with Zero Data Retention, and we never train models on customer data. Access follows your existing user permissions.
What happens when a model fails—and who catches it?
Large language models are probabilistic and inherently fallible. That is why we wrap every model in deterministic validation algorithms and automated sanity gates. If transcription clarity or extraction confidence drops below strict tolerances, the system flags the issue directly to the operator rather than hallucinating or proceeding with corrupt data.
What prevents resource runaway or budget spikes?
Every query pipeline and worker thread enforces hard token limits, cost caps, and circuit breakers. Systems cannot enter runaway recursive loops or accumulate unexpected API overhead. Latencies and budget thresholds are monitored with real-time alerting.
The Autonomy Ladder
How deeply should a workflow be automated? We always position operations at the lowest required risk tier:
Caliper does not build systems that interact with your clients unattended.