AI Chat Interface
A secure, evidence-backed conversational experience with first-class citations, structured outputs (tables, formulas, figures), and permissioned sharing tailored to business audiences.
Trusted AI operations
Operationalize AI workflows you can explain, audit, and improve.
optAIze is a control plane for AI systems that must be traceable, evaluatable, and governed. It turns AI from demos into dependable production infrastructure.
Every output is grounded in enterprise data, every run is measurable, and every decision is defensible when it matters.
Built for regulated teams
Trust isn’t optional in production AI.
optAIze keeps your workflows accountable with citations, access control, lineage, and repeatable evaluation. You can explain what happened, reproduce it, and prove it over time.
Why AI systems fail in production
Most AI deployments break when they leave the demo environment. Outputs can’t be reproduced, decisions can’t be explained, and teams lose trust in the system.
Auditability gaps
Without citations, lineage, and run history, it is impossible to defend a decision to auditors or leadership.
Repeatability breaks
If outputs cannot be replayed, you cannot debug failures or validate improvements over time.
Explainability debt
Black-box systems erode confidence. Teams need clear reasoning paths and the ability to inspect inputs and sources.
Product pillars
optAIze is composed of five integrated subsystems that make AI workflows observable, evaluatable, and governable.
AI Workflow Operations
The control plane for debugging, measuring, comparing, and re-running workflows with evaluation and regression testing.
AI Workflow Serving
Deterministic runtime execution with REST APIs for synchronous and batch invocation, designed to integrate with existing systems.
AI Trace & Run Intelligence
End-to-end traces, run metadata, captured inputs and outputs, and replay support for audits and investigations.
AI Document Intelligence
Versioned document ingestion with taxonomy-driven indexing, OCR, preserved tables and figures, and citation-ready lineage.
How it works
A straightforward flow that keeps AI systems grounded, measurable, and accountable.
1) Ground workflows in trusted documents
Ingest and version the sources that matter, with ACLs and lineage preserved for every document.
2) Compose workflows with clear inputs
Define the steps, prompts, datasets, and evaluation criteria so intent and constraints are explicit.
3) Execute and evaluate continuously
Run workflows deterministically, measure outputs, and compare changes across models or data versions.
4) Inspect, replay, and govern
Trace every decision, replay runs, and maintain audit trails for enterprise oversight.
Trust and governance by design
optAIze treats governance as a core system feature, not an afterthought.
Citations and source control
Outputs are tied to their sources with links and citations, so users can verify and inspect evidence.
ACLs and data boundaries
Access controls are enforced across documents, workflows, and outputs to keep data boundaries intact.
Lineage, replay, audit trails
Every run captures inputs, outputs, and decisions so teams can replay results and answer governance questions.
Enterprise deployment & cloud trust model
optAIze is designed for enterprise security reviews and data residency requirements without sacrificing usability.
Deployed in your Azure environment
optAIze runs inside customer-owned Azure subscriptions, with document content, indexes, and extracted artifacts stored in customer-controlled storage.
Security controls stay intact
LLMs are invoked through Azure-hosted services under enterprise security controls, with integration into existing identity, network, and security policies. No customer data is used to train foundation models.
Use cases in enterprise and regulated environments
Designed for teams that need defensible AI outcomes, not just fast prototypes.
Policy and regulatory analysis
Summarize and compare regulatory texts with traceable citations and clear provenance.
Risk and compliance reviews
Evaluate workflows with repeatable testing and audit trails that support internal review.
Knowledge operations in high-stakes domains
Provide staff with evidence-backed answers while preserving access controls and document lineage.
Operational workflow automation
Run deterministic AI workflows with measurable outcomes and continuous evaluation.
FAQ
Answers for skeptical enterprise buyers evaluating AI systems.
optAIze keeps citations and document links attached to outputs with lineage so reviewers can inspect the evidence and context.
Each run captures inputs, outputs, and metadata, enabling replay and comparison across model or data changes.
No. optAIze provides the control plane and observability needed to operate AI systems. Engineering judgment remains central.
optAIze supports evaluation and regression testing so teams can compare outputs across prompts, models, and datasets before rollout.
optAIze is deployed within customer-owned Azure subscriptions, integrates with existing identity and network policies, and keeps document content in customer-controlled storage.