Enterprise data and AI platform

From scattered
data.To decisions you can trust.

One governed platform for ingestion, transformation, ML, APIs, and operations, so your AI starts on a single trusted source. One contract, one upgrade path, and no stack to stitch together first.

Request a demo

Connects to the stack you already run
Ingest, model, serve, and build agents on the same data
Nothing has to be replaced on day one

SOC 2 Type II · ISO 27001 · GDPR assessed

Examined by Accorp Partners, QRO Certification and Scrut.

10+ enterprises in production

Air-gapped, on-premises, or in your own cloud.

2,000+ connectors, 40 copilots, 15 modules

Seventy executable compliance controls. All of it on one contract.

The problem

Nobody set out to build this stack.

It arrived one sensible purchase at a time. Every tool solved its own problem and handed you a new one: the seam between it and the next.

Most enterprise data teams run a stack of separate tools and own every join between them. DataByte replaces that with one governed platform covering ingestion, transformation, ML, APIs, analytics and governance, deployed on infrastructure you already control: your cloud, your own data centre, or fully air-gapped.

Side by side: without DataByte, seven separate tools joined by dashed lines you keep working; with DataByte, one platform cycling through get data in, make it useful, put it to work and keep it trusted. — The joins between the tools are the problem.

The platform

One integrated platform. One contract.

Browse the modules

Every module is production-grade on its own. Together they share one data model, one catalogue, one security model and one operational surface. This is the only section on this page that makes that argument.

Ingestion

Data Ingester

Move data in at any cadence: scheduled batch, on demand, or change data capture that streams every insert and update as it happens.

Batch
CDC
Advance ETL

Integration

Integration Connector

Connect any two systems without a custom project. Build the flow on a visual canvas, test it before it goes live, and run it with approvals attached.

Visual flows
Open standard
Governed

Processing

Transformer

Build transformation pipelines on a visual canvas or in a notebook, whichever suits the person doing the work. One engine for batch, streaming, and on demand.

Visual canvas
Spark
Streaming

Intelligence

ML Studio

Take a model from data preparation to production in one place. AutoML and experiment tracking, one-click deployment as a versioned API, drift monitoring after go-live.

AutoML
Drift
REST

Intelligence

Agent Studio

Build conversational and autonomous agents against the governed model rather than an export of it. Every agent answers inside the permissions of the person asking.

Conversational
Autonomous
Governed

Intelligence

Forecaster

Forecast demand, capacity, or cash with 25+ time-series algorithms. Scheduled runs, accuracy dashboards, and side-by-side backtests, so you can see which model to trust.

Time-series
Backtesting
Scheduled

Intelligence

Anomaly Detector

Catch the problem while it is still small. Continuous learning on live SQL, Kafka, webhook, and API streams, with alerts that carry the data that triggered them.

Near-real-time
Kafka
Self-learning

Operations

Sherlock

Root cause analysis that runs itself. No-code decision trees isolate the failing component, trigger the fix, and verify recovery before the incident is closed.

Root cause
Auto-remediation
No-code

See use cases in depth

Intelligence

AI that starts on data you can already defend.

See the copilots Agent Studio

Copilots and agents here read the governed model itself, never an export of it, answer inside the permissions of the person asking, and run on models hosted on your own infrastructure.

40 copilots included

One on every stage of the platform, each reading live metadata as it stands now.

Agent Studio

Build conversational and autonomous agents of your own against the same governed model the copilots use.

Inside the asker’s permissions

An agent answers within the permission model of the person asking, not a service account with its own reach.

Agent operations

Telemetry, versioned prompts and release control for every agent you run, so a degraded agent is visible before someone complains.

Forecast and detect

Time-series forecasting, drift detection after go-live, and deviation on live streams as they arrive.

Diagnose and resolve

Sherlock traces an incident to its cause. Sentinel works on the failures nobody wrote a rule for.

Resolve, then authorise, then answer.

Semantic Ontology

Every module speaks one business language.

How the ontology works

The ontology is the layer everything else on this page stands on. It is why a dashboard and an agent give the same answer, why policy can be written against a business object, and why the AI above is grounded in something a person signed off.

Business objects, not tables

Orders, Customers and Network Elements become versioned definitions carrying their own relationships, APIs, lineage and policy.

One definition, everywhere

Dashboards, APIs and agents resolve the same name through the same catalogue, so two answers to one question agree.

Policy on the object

Access is evaluated against the business object a person is asking about, so the table underneath it never has to be named in a policy.

The reason the AI holds

Agents are grounded on these definitions. Without them an assistant is guessing confidently about tables it has never seen.

One definition, read by every module and agent.

Security

Hardened before you receive it.

Read the security model

Every module inherits the same policy model, the same audit trail and the same catalogue. There is no hardening project between installation and production.

Three enforcement layers

Platform, module and data-level enforcement, evaluated in order, with no gap between them for a request to fall through.

Row and column level

Access narrows to the row and the column a person may see, not only to the table they may open.

A decision, not a config file

Open Policy Agent evaluates each request against the business object, so authorisation is reasoned at the moment of the request.

Encrypted in transit and at rest

Data is protected on the wire and on disk, under keys and a residency you choose.

One place to administer

Users, roles and permissions are managed once and apply to every module.

Independently assured

SOC 2 Type II, ISO 27001 and a GDPR control assessment, carried out by firms that do not work here. Report under NDA.

A request clears every layer or it does not run.

Governance

Governance is how it is built, not a module you switch on.

Explainability Fabric

Because every module writes to one catalogue, one lineage graph and one audit trail, the evidence an auditor asks for is a query rather than a project.

Chained audit trail

Every action is recorded with what authorised it, chained so any later alteration is detectable.

End-to-end lineage

Every asset and every hop, across modules that used to be separate products with separate lineage graphs.

Compliance as code

Seventy executable controls mapped to SOC 2, ISO 27001, GDPR, PCI DSS, SOX and the CIS Kubernetes Benchmark.

Classification on discovery

Sensitive fields are tagged as assets are found, so a GDPR question starts from metadata the platform already holds.

One catalogue

One inventory of every asset and its lineage, so no spreadsheet has to reconcile a catalogue per tool.

SMART in every module

SLAs, monitoring, actions, rules and traceability, uniform across the platform, in every module, on day one.

Evidence produced by doing the work.

Ownership

You own the deployment, the data and the exit.

The platform runs on infrastructure you control, on standards your team already operates, under one agreement. Leaving is an engineering exercise with no negotiation attached.

Runs inside your walls

Any cloud, your own region, on-premises, or fully air-gapped, on Kubernetes you already know how to run.

Nothing calls home

No data comes back to us and there is no dependency on a vendor cloud to keep the platform working.

Open standards underneath

Apache Spark, Kubernetes and Open Policy Agent. No proprietary runtime only one company knows how to operate.

Portable integrations

Integration routes are standard Apache Camel YAML, so what your team builds stays readable outside the platform.

One contract

Connectors, modules and copilots come with the platform, on one licence.

Your models, your hardware

Self-hosted models keep an air-gapped deployment air-gapped on the day you add AI to it.

Getting there

You do not have to replace anything on day one.

DataByte connects to the stack you already run. It closes the seams first, then takes over the pieces you choose to hand it, at whatever pace your contracts and your people allow.

Step 1

Connect what you have

Two thousand connectors reach the systems you already run. Nothing is decommissioned, and nothing has to move.

You get one catalogue and one lineage graph across tools that never spoke to each other.

Step 2

Run both and compare

Publish the same numbers from the old estate and the new one for a full reporting cycle. Sign off on the variance before anything is switched over.

The parallel run is the proof, not the risk.

Step 3

Retire on your schedule

Tools come out when their contracts end and their workloads have somewhere to go.

One renewal at a time, in the order that suits your budget rather than ours.

Some customers stop after the first step and keep everything they own. That is a supported outcome, not a failed sale.

Where you sit

The same platform, four different reasons to want it.

What DataByte replaces depends on the chair. Each of these goes to the argument written for that seat.

Consolidate the stack without a two-year migration, on infrastructure you already run.

CIO / CTO

See the platform

Integrations

2,000+ connectors, and none of them billed separately.

Databases, warehouses, cloud storage, streaming, SaaS, BI and file formats. Drag-and-drop by default, custom code when a source demands it, and the same governance on every one of them.

280+ SaaS connectors

Read and written the same way, so permissions and lineage carry across every one.