Pre-built compliance frameworks, deployment playbooks and reference architectures for the sectors with the most complex requirements — and the least tolerance for moving data into somebody else's cloud.
Air-gapped deployment, CMMC and FedRAMP-aligned governance, classified data handling.
Real-time fraud detection, SOX compliance and trade analytics at sub-millisecond latency.
HIPAA-native pipelines, on-premises PHI processing, AI diagnostics without cloud exposure.
OT/IT convergence, predictive maintenance and grid analytics on edge infrastructure.
Network analytics, churn prediction and real-time streaming from billions of events daily.
Demand forecasting, customer 360 views and supply chain intelligence at scale.
Factory IoT analytics, quality-control ML and operational data unification on-premises.
Content recommendation AI, rights management and viewer analytics across all platforms.
Each of these is assembled from components that exist in the product today — a named trigger, a named detector, a named model. The “built from” line under every card tells you exactly which ones, so you can check the claim against a demo rather than take it on trust.
Incoming documents are read, classified by sensitivity and routed to the right clearance tier — with the reasoning written to the audit log rather than lost in a queue.
Every deployed model carries its training run, its version, its promotion stage and the policy that allowed each individual call.
Score transactions as they land and open a case, instead of discovering the pattern in next month’s batch report.
The agent answers in the bank’s own vocabulary, because the glossary is a graph with typed relationships rather than a list of terms.
Summaries are generated inside the hospital’s own data centre, and protected health information is caught before it reaches any model.
A model proposes the labels, a clinician corrects them, and the corrected set is preserved with its train, validation and test splits for the next round.
OpenTelemetry collectors stream sensor data continuously; a deviation opens a work order rather than an email.
Corrosion, vegetation encroachment and insulator damage detected from survey photography, with the new model compared against the incumbent before it takes all the traffic.
A persistent LLM agent that can look up real systems rather than guessing from a knowledge-base article.
One gateway on the demo platform has handled 5,071 requests and 22.3 million tokens. Per-user budgets stop one team spending the quarter in a week.
Generate attributes, descriptions and tags directly from supplier images and PDFs, instead of paying for them to be keyed in twice.
Prompt-injection and PII detectors sit in front of every call, and every response carries a header saying it was AI generated.
Hard-hat detection on camera feeds, with the model pulled into your own registry rather than called over the internet.
Ask the manual a question and get the paragraph, on a plant network with no internet dependency.
Decades of audio and video become searchable text with timecodes, so the archive is an asset rather than a cost.
Split live traffic between the incumbent and the challenger and read the latency percentiles before committing.
Several of these run on our demonstration platform right now, including the hard-hat detection model, the banking ontology, the SharePoint document-compliance workflow and the live traffic split. Ask to see any of them in the demo.