FlashQuery runs where your data lives. As your enterprise AI control plane, it connects applications to models, enterprise knowledge, and governance policies — so your team ships AI features in weeks, not months.
Trusted by forward-thinking enterprises
Deployed across regulated industries, SaaS platforms, and private data centers
— where data sovereignty isn't optional.
Organizations adopting generative AI face systemic challenges that models alone can't solve. The real barriers are integration, governance, and control.
Sensitive enterprise data cannot leave your security boundary. Direct LLM API calls risk exposing proprietary information to external providers.
Regulated industries need audit trails, policy enforcement, and provenance tracking. Ad-hoc AI stacks have no centralized controls.
Building AI infrastructure from scratch delays AI feature delivery by months. Product teams need a ready-made platform, not a science project.
Building isolated AI pipelines per customer tenant doesn't scale — it multiplies infrastructure, data bleed risk, and engineering debt with every new customer.
Enterprise AI must be reliable. Without validation, and grounding, AI outputs can erode customer trust, increase churn risk, and create liability.
Betting your AI architecture on a single model provider creates fragile infrastructure. One pricing change or deprecation breaks everything.
FlashQuery sits between your applications and AI infrastructure — orchestrating retrieval, enforcing policy, and abstracting model complexity into simple, governed APIs.
Your apps invoke assistants or AI tasks through a standard API — no direct model calls, no custom RAG code.
FlashQuery authenticates the request, resolves tenant and user context, and applies FlashGuard governance policies (your centrally-authored AI ruleset).
Knowledge bases are queried, vector + structured data is retrieved, and context is assembled within authorized data boundaries.
The generation model produces a response; a secondary model evaluates accuracy against retrieved context before anything reaches your users.
Outputs are filtered, scored, and returned — with full trace, metrics, and policy event logging so your compliance team has everything they need.
A unified platform that replaces fragmented AI tooling with enterprise-grade orchestration, governance, and observability.
Managed ingestion, vector indexing, hybrid retrieval, and context assembly across enterprise data sources. AI responses grounded in authoritative data.
Route between self-hosted or commercial LLMs without application changes. Swap models, add fallbacks, and stay vendor-agnostic by design.
Ingest, index, and manage enterprise data sources with full provenance tracking. AI responses are grounded in your authorized content — with source traceability built in for audit and compliance.
Dual-model validation evaluates AI outputs against retrieved context before delivery, producing confidence scores and reducing hallucination risk.
Role-based data access, tenant isolation, and in-boundary execution. Data stays in your environment; models access only authorized context.
FlashGuard lets you define PII filtering, content restrictions, prompt controls, and output constraints centrally. FlashQuery enforces them locally within your infrastructure on every AI interaction.
Full traces, metrics, evaluation scores, and policy events for every AI request. Dashboards, audit logs, and insights to monitor and improve AI behavior.
Map enterprise identities into fine-grained AI permissions. Isolate tenants, scope knowledge bases, and enforce least-privilege access at every layer.
Every AI interaction executes as a governed workflow — not a raw model call. PII filtering, jailbreak detection, and policy enforcement run automatically in the interaction path, so applications inherit protection without building it themselves.
Whether you're a SaaS or software vendor, an enterprise, a data center provider, or a technology partner, FlashQuery adapts to your architecture and requirements.
Your organization has valuable proprietary data and real accountability requirements. FlashQuery runs inside your infrastructure, keeping data exactly where it belongs — while embedding audit trails, policy enforcement, and traceability directly into the AI execution path.
You need to ship AI features fast, across a multi-tenant SaaS architecture, while keeping customer data isolated and your compliance posture intact. FlashQuery is the AI backend that scales with your product.
Every client engagement shouldn't start from scratch. FlashQuery gives your AI practice a reusable architecture foundation — reducing delivery risk, accelerating timelines, and providing built-in governance your clients expect.
Your customers' data already lives in your facilities. When they adopt AI through external cloud services, you lose architectural relevance. FlashQuery lets you bring governed AI to where the data already resides.
FlashGuard is the cloud-based governance console that pairs with every FlashQuery deployment. Define AI policies centrally in FlashGuard — enforce them locally within your infrastructure through FlashQuery — and maintain full visibility across all deployments.
From request to response, every AI interaction follows a consistent, governed, and observable pipeline.
Application invokes an assistant or AI task via API
Authenticate, resolve tenant context, apply governance rules
Query knowledge bases, assemble context from authorized sources
Model produces response; secondary model evaluates accuracy
Filtered, scored, and logged — with full trace and audit trail
FlashQuery isn't a model gateway or a RAG library. It's the governed AI substrate that becomes part of your enterprise architecture.
APIs give you model access. FlashQuery adds retrieval, identity, governance, and observability — everything you need for production AI.
Vector-DB-centric stacks handle retrieval. FlashQuery adds policy enforcement, multi-tenancy, model abstraction, and evaluation on top.
Gateways route model calls. FlashQuery governs data, context, and outputs — not just traffic.
Custom platforms take months and lack standardization. FlashQuery ships in weeks with governance, observability, and multi-tenancy built in.
Hear how forward-thinking technology leaders are thinking about governed enterprise AI.
"While AI projects move at unprecedented speed, traditional governance processes are operating at yesterday's pace."
OneTrust
"One false product recommendation or legal citation can destroy trust that took years to build. Customers don't distinguish between 'The AI got it wrong' and 'Your brand published false information.' It's your credibility on the line."
Nasuni
"It's critical to have that observability and be able to go back to the audit log and show what information was provided at what point. You have to know if it was a bad actor, or an internal employee who wasn't aware they were sharing information or if it was a hallucination. You need a record of that."
Airia
"Last year, organizations were focused on escaping rising costs. This year, they are focused on avoiding regret. IT leaders want automation that reduces workload, architectures that support hybrid reality, and the freedom to change course as needs evolve."
Parallels
"Organizations want AI they can depend on to act predictably, explain its decisions and stay accountable as it takes on more work. AI agents built on a foundation of proven, deterministic workflows will ensure every action is grounded in predictable, governed and auditable logic."
ServiceNow
"AI innovation is advancing faster than most enterprises can formalize controls, forcing teams to scale technology and governance simultaneously."
Plex
Integrate AI securely, govern it completely, and deploy it wherever your data lives. Schedule a personalized demo.