You picked the best engine for each job, and that was the right call. The
cost turns up later, in the scheduling, dependency logic, and monitoring you
now maintain four times over.
A scheduler per service
ADF triggers, Databricks jobs, Function timers, and cloud schedulers each live in their own portal. Nothing shares a timeline, so nobody can say what ran when without checking each one.
No dependencies across platforms
Making a Databricks notebook wait on an ADF pipeline turns into a webhook, a queue, and a runbook no-one wants to maintain.
Tasks get rebuilt, not reused
The same steps, parameters, and schedules get recreated for every team, environment, and project. Because none of it is shared, a fix in one place rarely reaches the other five.
No single operational truth
Every platform keeps its own logs, run status, and audit trail. Answering "what ran, when, and why did it fail" means opening four dashboards and lining up timestamps by hand.
The jobs you already have become reusable building blocks. Nothing has to be
rewritten to get there.
- 1
Connect
Register your Azure, Google Cloud, and AWS platforms, then point Polysync at your secret vault: Azure Key Vault, AWS Secrets Manager, Google Cloud Secret Manager, or HashiCorp Vault. If you would rather not link one, Polysync can hold the credential in its own managed Key Vault.
- 2
Discover & import
Polysync reads each connected platform and imports its pipelines, notebooks, and functions, parameters included, as reusable job blueprints. Add your own inputs and outputs with default values for the tasks built on top.
- 3
Orchestrate & schedule
Build tasks from those blueprints, draw dependencies across platforms, and attach a schedule. Run it by hand first to prove it works. All of it is configuration, so there is nothing to compile, package, or redeploy.
- 4
Monitor
Every run, retry, and outcome lands in one execution history, alongside analytics dashboards and an inline dependency graph that shows where each execution sits.
Your execution engines stay exactly where they are. What Polysync takes off
your plate is the engineering cost of keeping them in step.
Jobs, tasks, dependencies, and schedules are stored as
configuration, not code. That is what lets one workspace
carry thousands of executions a week without quietly becoming a codebase of
its own.
Cross-platform dependencies
Wire tasks together across every connected platform, whether they sit in the same cloud or three different ones, with On Success, On Failure, On Completion, and On Skipped triggers. Circular dependencies are detected and blocked before anything runs.
Visual schedule builder
Pick a frequency and Polysync writes the schedule for you, so there is no syntax to learn. Each one shows a plain-English summary, a preview of its next three runs, and the timezone it follows. Attach as many schedules to a task as you need and switch each on or off independently.
Concurrency & rate limits
Keep peak batch windows from tripping API throttles. Set concurrency caps and leaky-bucket or rolling-window rate limits, per platform or globally.
Live monitoring
Schedules, the dispatch queue, and every execution refresh on a live 30-second cycle. Filter by status or time range, follow a retry chain back to its first attempt, and open the dependency graph on any run to see exactly what it was waiting for.
Auto-discovery & parameter mapping
Connect a platform once and Polysync imports its pipelines, notebooks, and functions with their parameters. Pipe output values from a parent task into a child task, even when the two run on different platforms, with no glue code.
Polysync Copilot sits inside the Setup Studio and can read your workspace and
build in it. The interesting part is not that it can act — it is
what it is not allowed to do without you.
Ask in plain English
Questions are answered from your actual configuration rather than a generic manual: which tasks run on a platform, what a schedule does next, why a run was waiting, how last week's executions went.
It does the setup work too
Register a platform, import its jobs, build tasks from them, wire dependencies, attach a schedule, create a contention profile, or check a secret vault connection — described in a sentence instead of clicked through a form.
Nothing changes until you approve it
Eleven of its actions change your configuration, and every one of them is staged as a proposal, not executed. You see what it intends to do and approve or reject it. An unanswered proposal expires after ten minutes.
Running a task costs money, so it asks
The assistant can start a task run on demand, which consumes your own cloud resources. That is treated like any other change: it proposes the run, names the task, and waits for you.
Your administrator can switch it off
The Copilot is a per-organisation setting an administrator controls. Turn it off and the assistant disappears for everyone in your workspace — no per-user cleanup, no partial state.
It only ever sees your workspace
Every question and every action is scoped to your own tenant and runs under your signed-in identity, so the assistant cannot reach another customer's configuration or step outside what you are allowed to do yourself.
It treats its own findings as untrusted. Pipeline names,
descriptions, and imported values often come from systems Polysync does not
control, so the assistant is instructed to read them as data and never as
instructions. Text smuggled into a pipeline name cannot talk it into an action.
Your conversation lives only as long as your session. It is not written to the
database, and it is never used to train an AI model.
Whatever the vendor, every connected service is registered, discovered, and
run the same way.
Microsoft Azure
Azure Data FactoryAzure DatabricksAzure FunctionsAzure Logic AppsAzure Synapse PipelinesMicrosoft FabricPower BIAzure Kubernetes ServiceAzure BatchAzure AI FoundryAzure AI Foundry ProjectAzure OpenAISQL Database
Google Cloud
Google Cloud ComposerGoogle Vertex AIGoogle Cloud FunctionsGoogle Dataflow
Amazon Web Services
AWS GlueAWS LambdaAWS Step FunctionsAmazon SageMakerAWS Batch
Secret Vaults
Azure Key VaultAWS Secrets ManagerGoogle Cloud Secret ManagerHashiCorp Vault
Credentials stay in your vault. If you would rather not
link one, Polysync can hold them in its managed Azure Key Vault instead.
Either way they are encrypted at rest and read only at dispatch time,
never kept in application memory or written to logs.
One billing line for orchestration.
Your Azure Marketplace subscription covers Polysync itself; the pipelines it
orchestrates keep running on your own cloud account, billed as usual.
Polysync is general-purpose orchestration, but the same handful of patterns
come up again and again.
Enterprise data warehouse loads
Chain ADF ingestion, Databricks transformations, and Synapse or Fabric publishing into one nightly DAG, with retries and rate limits handled by the dispatcher.
ML and AI pipelines
Sequence feature engineering on Databricks, training on Vertex AI or Azure AI Foundry, and batch scoring on Azure OpenAI or Functions, with parameters passed between stages and no glue code in between.
Multi-cloud orchestration
Coordinate workloads spanning Azure, Google Cloud, and AWS from one DAG. A Cloud Composer job can trigger an ADF pipeline on success, with output parameters crossing the cloud boundary automatically.
Migration in flight
Orchestrate Step Functions, Glue, Lambda, SageMaker, and Batch alongside their Azure or Google Cloud counterparts in one DAG. Cut over service by service without rewriting orchestration.
Compliance and audit reporting
Every run, parameter, retry, and outcome is recorded in your tenant's own schema. When an auditor asks what ran, when, and with which inputs, the answer is a query rather than an excavation. The evidence SOX and APRA CPS 234 reviews ask for is already there.
Consolidating fragmented schedulers
Replace ADF triggers, Databricks job schedules, Function timers, and native cloud schedulers with a single scheduler that respects cross-platform dependencies and contention limits.
Polysync is a managed service, so the platform underneath it is our problem
rather than yours. Here is exactly what that means, without the adjectives.
Your data stays in Australia
Everything Polysync stores — your platform connections, your schedules, and the history of every run — is held in Microsoft's Australian data centres. None of it leaves the country.
Attacks blocked before they reach us
Every request to Polysync passes through Microsoft's enterprise web firewall before it reaches the application. Known attack patterns are blocked automatically, and Microsoft keeps those defences current rather than us.
No new passwords to manage
Your team signs in with the Microsoft work accounts they already have, so your existing multi-factor authentication and access rules apply unchanged. Polysync never sees or stores a password, and when someone leaves, disabling their Microsoft account removes their Polysync access at the same moment.
Your data is separated, not just filtered
Each customer's information sits in its own dedicated area of the database rather than being mixed into shared tables and filtered by a customer column. It is encrypted on the way to us and encrypted again at rest.
Credentials kept in a locked vault
Polysync's own credentials live in a dedicated Microsoft vault that cannot be reached from the public internet. Our services prove who they are to each other using Azure's built-in identity system, so there are no shared keys sitting around to be copied or leaked.
Backups you can actually restore
We can put the database back to any point in the last 35 days, and we keep weekly, monthly, and yearly copies well beyond that. More to the point, we have carried out a real restore and timed it rather than assuming the backups would work.
The assistant has boundaries too. Polysync Copilot runs
on Microsoft's AI service inside our own account, so your questions are
never used to train anyone's AI model, and the conversation is kept only
for the length of your session rather than stored afterwards. Polysync
is currently working through Microsoft 365 App Certification.
Orchestration sits in the middle of everything you run overnight, so it
matters who is behind it and what it is made of.
Australian registered company
Polysync is built and owned by Polysync Data Solutions Pty Ltd (ABN 87 683 785 686), an Australian registered IT consultancy. You are contracting with a local company under Australian law, bound by the Privacy Act 1988 and the Australian Privacy Principles, and the product is shaped by consulting work on real data platforms rather than by a roadmap written at a distance.
Built with Microsoft technology
Polysync runs entirely on Microsoft Azure and is built end to end with Microsoft's own development tools, database, and AI services. It was built for Azure from the start rather than moved there later. In practice that means your team signs in with the same Microsoft work account they use for Teams and Outlook, and your IT admins grant or remove access from the same Microsoft admin console they already use. There is no separate user list and no new password to issue.
On the agreement you already have
Polysync is a transactable Azure Marketplace subscription, so it arrives as a line on the Azure bill you already receive. There is no new vendor to onboard, and the pipelines Polysync orchestrates keep billing to your own cloud accounts exactly as they do today.
Nothing gets replaced. The engines you already pay for
keep doing the work. Polysync adds one schedule, one dependency graph,
and one set of access rules on top of them, so Data Factory, Databricks,
Fabric, and your native cloud schedulers carry on exactly as they are.
Not a quickstart and a support address. Every platform Polysync connects to
and every job type it runs has its own guide, covering what to fill in,
which permissions the connection needs, and what each parameter does.
No account, no trial, no sales call — the whole library is
open before you sign up.
One guide per connection
A guide for each of the 22 services and each of the 4 secret vaults, plus one for every job type behind them. They cover the authentication options, the exact permissions to grant, and the parameters that job accepts.
Searchable, not a PDF
Full-text search across the library returns the matching passage, not just a file name. Every topic has its own address, so you can send a colleague the exact page rather than the front door.
It follows you into the product
The guides are not a separate site you have to remember. Setup screens link straight to the relevant page, and the assistant reads from the same library, so an answer in chat matches the documentation exactly.
Evaluate before you commit. Read the guide for the
service you actually use and judge whether Polysync handles it properly
— before you spend a minute on setup.
Open the documentation
Connect a platform, import jobs with their parameters, wire dependencies
across clouds, attach a schedule, and watch every run in one view.
Deliver workflows faster
Your existing platform jobs become reusable building blocks. Teams assemble a workflow from parameters and defaults instead of rebuilding the same logic for every new project.
Reduce operational firefighting
Schedules, manual runs, retries, and concurrency limits all live in one place. When something breaks overnight, whoever is on call has one place to look.
Avoid building another internal platform
Most teams end up building some version of this themselves, then own it for years. Polysync is that layer, already built, and someone else keeps it running.
Your execution engines stay exactly where they are. What Polysync takes off
your plate is the engineering cost of keeping them in step.