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AI & Cloud Research and Infrastructure Company

Private by Design.
Intelligent by Purpose.
Secure by Control.

We build the control layer between your data, the cloud, and AI models — so you decide what stays private, what moves, and which intelligence gets used.

Request a briefingWhat we build
  • Control
  • Privacy
  • Security
  • Intelligence
control plane · routingstreaming

request

Summarise 41 sealed filings for matter 2291-B

  • classifyprivilege: high · residency: eu-central
  • routeslm-legal-7b · in-cluster
  • contextprivate rag · 41 docs · index-scoped
  • toolsread: matter-store · write: none
  • egressblocked by policy
containedNothing left the environment240 ms
Illustrative traces. Every route, redaction, and tool grant is decided by policy you author — and recorded whether it is allowed or refused.

The bottleneck

AI adoption is accelerating. Trust and control are what stall it.

Teams want AI on the data that matters most. Moving that data to someone else’s system is what makes it risky — and the six failures below all start there.

  • at the prompt

    Sensitive data exposure

    Every context window becomes a second, unaudited copy of your data.

  • at the vendor

    Loss of control

    Once data lands with a provider you inherit their retention, their region, their roadmap.

  • at review

    Compliance drag

    Each new model triggers a new review cycle, and delivery stalls behind it.

  • at the platform

    Cloud dependency

    One provider ends up holding the data, the models, and the pricing power.

  • on the invoice

    Cost that scales wrong

    Frontier tokens get spent on work a 7B model in your own cluster could finish.

  • in the supply chain

    Third-party risk

    Subprocessors change without notice, and the risk register never catches up.

Nobody should have to choose between capable AI and control of their data.

We make both possible.

What we build

Five layers of one system. You keep the keys to all of them.

Each layer is useful on its own and stronger together. Every one of them enforces the same policy set, so a rule you write once holds from the edge device to the frontier model.

Hybrid LLM models & systems

Every task goes to the model that should handle it.

One orchestration layer over small local models, open-weight models in your cluster, and frontier models behind a gateway. Sensitivity, latency, and cost decide the route — not a hard-coded provider.

  • Custom SLMs fine-tuned on your corpus
  • Open-weight models served in your own cluster
  • Frontier models reached through a redaction gateway
  • Per-task routing on privilege, latency, and cost
  • Deterministic fallback chains with no silent downgrade
  • Private RAG over indexes scoped per role

slm · open-weight · frontier · policy-routed

Edge device AI integration

Inference where the sensor is.

Models compiled down to the hardware already on your floor, in your vehicles, and in your instruments. Decisions land inside the control loop instead of waiting on a round trip.

  • On-device inference for robotics and instrumentation
  • Sensor, vision, and telemetry fusion at the source
  • Sub-50 ms control loops that survive a dropped link
  • Offline-capable model bundles with local fallback
  • Signed over-the-air model updates and rollback
  • Edge-to-core sync governed by the same policy set

on-device · offline-capable · signed ota

Cloud infrastructure

The platform underneath, built to your shape.

The unglamorous layer that decides whether any of this holds under load: environments as code, GPUs scheduled properly, storage and observability wired in from the first deploy.

  • Environments defined as code, reproducible per region
  • GPU scheduling, queueing, and autoscaling to zero
  • Vector, object, and warm-cache storage tiers
  • Tracing, evals, and per-team cost attribution
  • Data residency pinned per tenant and per workload
  • Cloud, on-prem, or hybrid — same control plane

iac · gpu scheduling · multi-region

Secure cloud infrastructure

Use the cloud without handing over control.

Security designed in, not bolted on. You hold the keys, the network boundary, and the audit trail — and you can prove all three to an auditor without asking us for a favour.

  • Encryption at rest, in transit, and in use
  • Customer-managed keys you can revoke unilaterally
  • Private networking, no public inference endpoints
  • Role-based, context-aware access on every call
  • Immutable audit trail across data, model, and prompt
  • Built for SOC 2, ISO 27001, HIPAA, and GDPR review

customer-managed keys · isolated · audited

Safe autonomous agent orchestration

Agents that act, inside a boundary they cannot cross.

Autonomy is a permissions problem before it is a model problem. Agents get narrow tools, hard budgets, and a gate in front of anything irreversible.

  • Tool permissions scoped per agent, per role, per run
  • Human approval gates on irreversible actions
  • Sandboxed execution with no ambient credentials
  • Step-level trace: every call, cost, and decision
  • Budget, rate, and loop limits enforced at runtime
  • Deterministic rollback and a documented kill switch

scoped tools · approval gates · rollback

Architecture

Your data. Your rules. Our control plane.

Sources connect on one side, model surfaces on the other. Nothing crosses without a decision, and every decision is written down.

Sources

  • Documents
  • Databases
  • Email
  • Files
  • APIs & tools
  • Sensors & devices
  • Applications & agentsWhat your teams actually touch.
  • Orchestration & routingChooses the model, enforces the policy.
  • RAG & knowledgeRetrieval scoped to the asker.
  • Model layerLocal, custom, open-weight, frontier.
  • Data layerPrivate by default. Never a training set.
  • InfrastructureCloud, on-prem, hybrid, edge.

Your data stays yours.

Model surfaces

  • Custom SLMs
  • Open-weight models
  • Frontier models
  • Agents & automation
  • Apps & workflows

  • Zero data leakage

    Data stays inside the boundary you define.

  • End-to-end encryption

    At rest, in transit, and in use.

  • Granular access control

    Role-based and context-aware, per call.

  • Audit & compliance ready

    SOC 2, ISO 27001, HIPAA, GDPR.

  • Deployment flexibility

    Cloud, on-prem, or hybrid — your call.

Where this matters most

Secure AI for the most sensitive work.

We partner with organisations whose data cannot be handed to a third party — and whose work is too valuable to leave AI out of.

  • Law

    • Case research
    • Contract analysis
    • Evidence organisation
    • Legal drafting
    • Knowledge systems

  • Medical

    • Clinical documents
    • Patient data analysis
    • Research intelligence
    • Imaging & reports
    • Secure workflows

  • Investigation

    • Evidence analysis
    • Document intelligence
    • Case linking
    • Open-source research
    • Secure data rooms

  • Robotics

    • Edge AI
    • Sensor intelligence
    • Autonomous systems
    • On-device inference
    • Low-latency control

  • Institutes

    • Research data
    • Knowledge hubs
    • Secure collaboration
    • Academic integrity
    • Private AI labs

From firms to institutes, we build secure AI systems that respect privacy and empower intelligence.

Where we are

Building the foundation.
Preparing for real-world impact.

We are building a secure, private AI infrastructure layer that lets organisations use multi-model AI through intelligent tooling, hard security guarantees, and domain-specific customisation.

80%

Backend infrastructure ready — core systems built, tested, and running in our private environment.

In build now
  • 01

    Backend infrastructure

    80% of core systems are running: secure architecture, APIs, and services.

    Running in our private environment

  • 02

    Agent tooling system

    Intelligent tooling that lets agents reason, act, and adapt inside the boundary.

    In active build

  • 03

    Fine-tuning & customisation

    Domain models trained on customer corpora for specific workflows.

    In active build

  • 04

    Tests & evaluations

    Large-scale evals for accuracy, reliability, and safety before anything ships.

    Continuous

  • 05

    Multi-modal inputs

    Text, image, video, audio, and sensor data as first-class model inputs.

    Text, image, audio live

Inputs we accept
  • TextNatural language inputs and conversations.
  • ImageImages, charts, diagrams, and visual data.
  • VideoVideo understanding, frame analysis, event detection.
  • AudioSpeech, audio signals, and acoustic understanding.
  • SensorIoT, sensors, logs, and real-world environment data.

Next: partner, deploy, transform.

Over the coming quarter we are deploying private AI infrastructure with a small set of partners, integrating domain models, and putting agent systems into real workflows.

  • Pilot deployments with selected partners
  • Domain-specific model implementation
  • Agent system integration and scaling
  • Continuous testing, evals, and optimisation

Why us

Five commitments we design against.

  • Security first

    Designed in, not bolted on.

  • Data sovereignty

    You own your data. Always.

  • Model agnostic

    Best model for the task, every time.

  • Future ready

    Modular architecture that scales with you.

  • Built for impact

    Powering mission-critical work.

Start a conversation

Tell us what your data is not allowed to do. We’ll design around it.

A briefing runs about 45 minutes: your data boundaries, the workflows you want to automate, and a candid read on what should stay local, what belongs in your cloud, and what a frontier model should never see.

Email hello@sentientvector.ai

Prefer to look first? The architecture and the five layers are both above — no form in the way.