Private by design. Governed by default..
Align models safely with human feedback
Run supervised fine-tuning and RLHF with full visibility into datasets, methods, and outcomes.
Learning is deliberate, auditable, and reversible.
Measure what matters before and after deployment.
Evaluate models against accuracy, consistency, and task-specific criteria using test sets and SME review.
Compare versions and catch regressions before production.
Production releases with version control.
Promote models from development to production with controlled configuration, rollback and environment isolation.
No silent changes. No unmanaged endpoints.
Test behavior with full transparency
Interact with deployed models and validate responses.
Runtime safety and compliance enforced
Detect and log policy violations and misuse at runtime.
Enterprise knowledge retrieval controlled.
Ingest documents and data into project-scoped knowledge bases.
Align models safely with human feedback
Run supervised fine-tuning and RLHF with full visibility into datasets, methods, and outcomes.
Learning is deliberate, auditable, and reversible.
Measure what matters before and after deployment.
Evaluate models against accuracy, consistency, and task-specific criteria using test sets and SME review.
Compare versions and catch regressions before production.
Production releases with version control.
Promote models from development to production with controlled configuration, rollback and environment isolation.
No silent changes. No unmanaged endpoints.
Test behavior with full transparency.
Interact with deployed models, inspect raw inputs and outputs, and validate responses with SMEs before approval.
Runtime safety and compliance, enforced.
Detect and log policy violations, PII exposure, toxicity, and misuse at runtime.Every request is traceable to rules, feedback, and outcomes
Enterprise knowledge, retrieval-controlled
Ingest documents and data into project-scoped knowledge bases with configurable retrieval, ranking, and context limits
AI moves from experiment to production months sooner, with built-in controls.
Governance, guardrails, and audit evidence are designed in, not bolted on.
Fewer failed pilots, fewer restarts, sustained executive sponsorship.
Human expertise is captured through dataset pipelines and HITL, becoming reusable AI assets not tribal knowledge.
You own the data, datasets, feedback loops, and tuned models.
Faster And Better
Domain Specific / Vertical AI
True Ownership
On-prem or private cloud. Your models. Your data. Your IP.
On-prem
AI must survive economic scrutiny before it ships.
Private cloud
Access and prepare enterprise data for AI workloads.
Hybrid-ready
Decision rights, audits and oversight by design.
No lock-in
Domain-trained models, integrated within core processes.
No black boxes
Every output is traceable. Every decision is defensible.
GenAI Foundry is built as a single control plane for governed AI execution. Vertical AI systems sit on top of this foundation, inheriting the same standards for governance, evaluation, and controlled learning. Same core. Consistent behavior in production.
InsurancGPT is a vertical execution layer built on GenAI Foundry. It brings insurance-native intelligence to underwriting, claims, policy, and compliance workflows — with evidence, auditability, and human control built in. Powered by GenAI Foundry. Designed for real insurance operations.
Additional regulated-industry verticals are in active development. Each new vertical reuses the same control plane and adds domain-specific intelligence. Same control plane. New domain intelligence.
One platform. Full lifecycle control. Built for regulated enterprises.
From raw data to training-ready datasets
Deliberate, governed model learning
Continuous evaluation with human oversight
Production releases with control
Transparent model testing for SMEs
Runtime safety enforced by default
Governed enterprise knowledge for AI
Reusable, approved prompts
If AI outcomes matter in your organization, the next step is clarity.
No pressure. No hype. Just measurable impact.