Integrate
Connect APIs, data feeds, documents and internal systems — including PDF and document intake — without custom plumbing.
Qriton Flow is the enterprise platform for private AI operations — deployed on your infrastructure, integrated with your systems, and accountable for every run. Dependable by design, and built to keep working.
In production today, operating a public media-intelligence service — every day, unattended. See it live →
Qriton Flow connects your sources, applies the right model under your policies, and delivers finished output to the channels your organisation already uses. The same platform serves a daily executive brief and a multi-stage intelligence pipeline — flexible where your needs differ, consistent where they don't.
Connect APIs, data feeds, documents and internal systems — including PDF and document intake — without custom plumbing.
Apply AI where it earns its keep: summarisation, classification, extraction, translation and drafting — governed by your policies and budgets.
Publish to the web, distribute by email, hand off to downstream systems, or produce finished documents — automatically, on schedule.
Guided setup from curated starting points — choose a workflow, complete the few fields that matter, and it is scheduled and running in minutes. No specialist required.
Tell the platform what you need — "summarise these feeds every morning and publish the brief" — and it drafts the workflow for you, ready to review, adjust and run.
When a workflow carries your reporting, your communications or your compliance obligations, "usually works" is not a standard. Qriton Flow guarantees that every scheduled task executes exactly once, recovers automatically from failure, and leaves a complete record of what it did.
Across retries, restarts and redundant servers, a task runs a single time. No duplicate communications, no double postings, no repeated transactions.
Interrupted work is detected and resolved within seconds. A failure is reported and contained — never left hanging for someone to find.
Every run maintains a complete operational record — what ran, when, and with what result — available for review at any time.
Use leading cloud models where quality matters most, and private models on your own hardware where confidentiality or cost governs. Qriton Flow treats every model the same — so your strategy can evolve without re-engineering, and no provider becomes a dependency.
| Model | Deployment | Cost model | Where it fits |
|---|---|---|---|
| HLM-Criticalbuilt for you, on your data | Your infrastructure | No per-call cost | A bespoke private model, commissioned on your own data — operates autonomously and builds your knowledge bases |
| Open-source modelsyour selection | Your infrastructure | No per-call cost | Private processing on open models, air-gap ready |
| OpenAIcommercial provider | Cloud API | Metered | Frontier quality for the most demanding tasks |
| Anthropiccommercial provider | Cloud API | Metered | Frontier quality and long-context analysis |
European by design. Qriton Flow deploys inside your own environment: the platform and the model operate where your data lives, and outbound access is governed by policy you control. What leaves the organisation is a decision — never a default.
Access, spend, content and conduct are governed by the platform itself — not by convention. The controls your security and finance teams require are built in, active by default, and enforced on every run.
Deploys behind your identity provider or zero-trust gateway, so your corporate sign-on and MFA policy apply before the platform is ever reached.
Passwordless sign-in for people and individually issued keys for systems — no shared credentials, no standing secrets.
Encrypted in transit throughout. At rest, data remains in your storage under your own encryption and key management — keys never leave your custody.
Spend limits per run, per day and per month, enforced before every model call. Private models carry no per-call cost at all.
Model output is checked against your policy before it is delivered — and stopped when it doesn't conform.
Built-in limits protect the systems your workflows touch, so automation never becomes the cause of an outage.
Unusual activity automatically suspends the workflows responsible and notifies your team — containment first, diagnosis second.
Residency by construction: the platform runs where you deploy it — your datacentre, your region, your jurisdiction.
Complete records of every run, retained on your terms and available for internal review or external audit.
Reporting is a delivery channel, not an afterthought. A workflow's output goes straight to a live web page, an email distribution or a finished document — on a stable address that updates in place, with no page for anyone to maintain.
A public media-intelligence service covering Romania, Bulgaria and Moldova — researched, written and published by Qriton Flow itself. Every edition on this site was produced and delivered by the platform, unattended.
See it liveOn infrastructure you control — your own server, your datacentre or your private cloud. The platform, the HLM-Critical model and the KB data engine are installed inside your environment and operate behind your own gateway. There is no multi-tenant service in the middle, and no Qriton-hosted copy of your data.
Not unless you decide it should. By default, workflows run against your internal sources and your private model, entirely inside your perimeter. Any outbound connection — to a cloud model, an external API or a publishing destination — must be expressly permitted by your policy. Every connection a workflow makes is recorded, so the answer to "what left, and when?" is always in the audit record, not in someone's memory.
All of the following, in any combination: HLM-Critical, a private model Qriton builds for you on your own data, running on your own hardware; open-source models of your selection, also fully local; and leading commercial providers such as OpenAI and Anthropic where frontier quality justifies a cloud call.
Workflows treat every model identically, so you can change your model strategy — or define an order of preference with automatic fallback — without re-engineering anything. If a cloud provider is unavailable or over budget, the workflow continues on the next model in line, including your private one.
HLM-Critical is a private model Qriton builds specifically for your organisation, trained on your own data and deployed on your own hardware. It is commissioned separately — not bundled with the platform — and once in place it carries no per-call cost, works without an internet connection, and never sends a token outside your organisation. It operates autonomously: it can create and maintain your knowledge bases itself, keeping them current as your data changes.
The KB data engine is the result: your organisation's own governed knowledge base — your documents and data, indexed and answerable inside your perimeter, available to every workflow as a first-class source. Together they let a complete workflow — question, reasoning, answer — run without a single external dependency.
Every scheduled task executes exactly once — enforced by the platform's execution control, not by convention. Duplicate triggers from restarts, retries or redundant servers are declined before they can act, so there are no duplicate emails, postings or transactions. If a run is interrupted, the platform detects it within seconds, marks it clearly and moves on — a workflow can never hang half-finished waiting for a process that no longer exists. And every run leaves a complete operational record of what it did and produced.
Three ways, all enforced by the platform. First, hard budgets: spend ceilings per run, per day and per month, checked before every model call is made — not reported after the invoice arrives. Second, model strategy: routine work can run on your private models at no per-call cost, reserving metered cloud calls for the tasks that need them. Third, anomaly response: unusual spend automatically suspends the workflows responsible and notifies your team.
No. A guided wizard sets up a working workflow from curated starting points in minutes — choose one, complete the few fields that matter, and it is scheduled and running. You can also simply describe what you need in plain language and the platform drafts the workflow for you, ready to review, adjust and run. Deeper customisation is available when your team wants it, but it is never the price of entry.
A workflow's output can publish itself: to a live web destination with a stable address that updates in place, to an email distribution, or as a finished document. There is no page to maintain and no manual assembly step. A production example runs today — a media-intelligence service publishing daily to a public site — which you can inspect at any time via the "See it live" link above.
The platform deploys behind your identity provider or zero-trust gateway, so your corporate sign-on and MFA policy apply before it is ever reached. Traffic is encrypted in transit; data at rest remains in your storage under your own encryption and key custody. Residency is a matter of construction, not contract — the platform runs where you deploy it, in your jurisdiction. And because every run is recorded end to end, you can evidence what your AI did — to an internal reviewer, an auditor or a regulator.
Request a briefing. We will walk through your use case, agree the deployment shape — your server, your datacentre or your private cloud — and stand up a pilot on your infrastructure with your own data. From there, the wizard and your first scheduled workflows do the convincing. Contact us to arrange it.
From a daily executive brief to a continuous intelligence operation, Qriton Flow runs it on your infrastructure, with your choice of model, under governance your security and compliance teams will recognise.