Enterprise AI,
On Your Terms
Bring GenAI into production
without risking your data, compliance, or IP.
FlashQuery is the control plane that lets product and engineering teams deploy copilots, RAG pipelines, and automation within your own environment; on-prem, in a private cloud, or with secure open-weight models like Llama 4.
95% of enterprise GenAI projects never make it to production.
Half fail before they ever leave the lab, not because the models don’t work, but because deploying them into production is the hard part. Most teams hit the same wall:
Data can’t leave the firewall
This blocks deployment when sensitive information is involved.
Compliance stops projects cold
Without built-in governance and auditability, production isn’t possible.
Performance breaks under real workloads
Models that look great in demos often fail to scale in real-world conditions
Infrastructure doesn’t scale
Brittle pipelines and manual workarounds make deployment costly and slow.
FlashQuery removes those barriers
It’s the control plane for deploying secure, production-grade GenAI inside the software you build, without compromising data security, compliance, or flexibility.
With FlashQuery, you can:
Run anywhere
Deploy GenAI on-prem or in a private cloud, with no data ever leaving your environment.
Use any model
Orchestrate open-weight or commercial LLMs without vendor lock-in.
Control and scale
Monitor performance, enforce governance, and scale confidently from Day One.
We make production-ready AI infrastructure simple, secure, and fast, even in the most regulated environments.
Core Features
Deploy Anywhere
Run on-prem or in a private cloud so sensitive data never leaves your environment.
Security & Compliance Built In
Governance, observability, and audit-ready controls from day one.
Model-Agnostic Architecture
Use open-weight or commercial models and switch anytime without lock-in.
From POC to Production, Fast
No brittle integrations. No re-architecture. Just launch in weeks, not months.
What People Are Saying About GenAI Challenges
Generative AI’s potential is undeniable, but the path to enterprise production is full of hurdles. FlashQuery exists to help teams solve the hard problems of trust, governance, and scale.
If we can't fully customize or govern the AI to fit our needs, it feels like we're letting someone else decide how our business should run. That's a level of risk I'm not comfortable with.
OpenAI is our brain, but tomorrow Google may come up with something — or another company. If we go all-in with GPT enterprise, or go with Co-pilot, we'll be locked into one ecosystem. DON'T WANT THIS!
Foundational models are not suitable for enterprise use, says Brian Demitros, innovation lead for data and technology at advertising network Dentsu. “They’re trained on the internet and often contain innacurate or misleading information,” he says. “You can’t simply use them out of the box and expect a level of accuracy needed to support critical decision-making. Customization is critical to get value out of them.
Seven in 10 executives believe enterprise use of generative AI means exposing company data to new security risks.
Organizations are seeing a dramatic rise in informal adoption of gen AI – tools and platforms used without official sanctioning.
Many organizations considering AI implementations are concerned about the potential loss of corporate data, a risk that weighs heavily on the minds of buyers.
More than three-quarters of CIOs in our survey reported they are concerned about the security risks of AI.
IT leaders can expect data issues, compliance hurdles and technology coordination chores when scaling generative AI.
There are a number of issues to solve before you go from pilot to scale... It's important to just set the frame and say, 'We see the honeymoon phase being over.’