Data quality at the source. Incoming. Operational. Traceable.
Data arrives from sources nobody controls, in formats that change without warning, on timelines nobody can slow down. Each item has to be shown to be complete and consistent before anything downstream relies on it. The engine checks it at the point of entry, surfaces what it cannot settle, and produces a record of every decision it made.
Representative interface, synthetic records. Not a screenshot.
- Check timing
- At the source
- Before downstream systems receive it
- Rule sets
- Written as code
- Versioned and auditable
- Uncertain items
- Routed to a person
- Nothing defaults silently
- Decision log
- Every check
- Rule version, result, and reason
Today
Seven places the work is currently manual
Every one of these is currently done by a person reading data. The later it runs, the more it costs to fix.
- Completeness
- Whether incoming data is whole: required fields present, values in expected ranges, volume matching what the source should have produced. Found on arrival, this costs a question back to the source. Found at analysis, it costs a re-run.
- Cross-system consistency
- The same entity described in three systems, with three different values for the same field. Which one is authoritative is a decision someone has to make. Without a rule, the last writer wins and nobody notices.
- Check coverage
- Which rules exist, what they cover, and what falls between them. Rules accumulate across teams and tools, and the gaps are usually found by the thing that breaks, not by a coverage map.
- Sensitive data handling
- Confirming that sensitive fields were handled correctly is a separate act from handling them. Trusting that the upstream step ran is not a check.
- Deduplication
- The same entity arriving under different identifiers, from different systems, or at different times. Deciding what makes two records the same record is currently done by inspection, which makes it inconsistent and slow.
- Integrity verification
- Whether data has been altered between its origin and its destination. Most pipelines carry no integrity signal, so this can only be measured from the data itself.
- Audit trail
- A complete record of what ran, when, against what version of what rule, and what it found. Without it, a question about what happened at a specific time requires reconstruction from logs and memory.
Coverage
Where the modules sit, and where they stop
Data travels from the source that produces it to the system that uses it, and most of that chain already belongs to the organisations running it. The modules cover one segment: between an item arriving and that item being fit to use.
The modules take incoming items, resolve them into typed outputs, check them, and find what each one relates to. Who interprets an item, and what they decide, does not change. No module makes a domain judgement, and none sits between a reviewer and their work.
Scroll the diagram sideways
What stays with you
- Reviewer workflow
- Assignment, adjudication, and the queues your reviewers work from. The modules route items to those queues and record decisions. They do not replace the workflow.
- Domain interpretation
- What an item means, and what the right response is, is decided by the people who own the data, under your procedures. The modules produce no domain finding.
- Systems of record
- Your database and downstream tools stay the systems of record. The modules run against them and hand items back to them.
- Your quality system
- Change control and release stay yours. The software runs under your procedures rather than beside them.
Configuration
What the configuration encodes
The modules carry no domain knowledge of their own. What makes them useful is the configuration: field maps, checks, thresholds, and routing rules that state, in your terms, what a correct item looks like. That configuration belongs to you and is versioned like code.
Each item below is scoped and written as an acceptance test before it is built. If one cannot be written as a test it does not enter scope.
- Item shape and completeness
- What a complete item looks like per type and per context: which fields are present, whether values fall inside specified ranges, and whether the item matches the expected set for its source.
- Cross-source reconciliation
- Incoming records, declaring systems, and destination stores frequently give different values for the same field on the same entity. The configuration names which source is authoritative when they disagree.
- Sensitive field verification
- Confirming removal or masking as a separate act from the removal itself. The check runs the same way regardless of who performed the upstream step.
- Duplicates and priors
- The same item arriving twice, under two identifiers, from two sources, or weeks apart. Identity rules state what makes two arrivals the same arrival.
- Provenance checks
- Whether an item has been altered between source and system of record.
- Rule coverage
- Which checks run against which item types, where each one runs, and what is deliberately not covered. A gap is a decision someone made, not something found during a review.
- Transfer integrity
- What arrived against what was sent, per batch, with an incomplete transfer raised at the point of entry.
- Query routing
- Which findings a source can resolve, which go to a data manager, and which stop an item from progressing. Routing is configuration, not code.
Downstream
Where the items go
A checked item earns nothing until the rest of the system can use it. The modules emit typed outputs, findings, and the evidence behind each one in a form a downstream system can take.
The connection is a named, versioned output scoped like any other part of the build.
Context
Built for auditability
The modules run under your quality system rather than beside it, with a complete audit trail and your team holding release.
A reviewer should be able to ask what ran, on which version, against which rule set, and receive a document rather than a reconstruction.
| Deliverable | Purpose |
|---|---|
| Test plan | Scope, approach and responsibilities for the test effort |
| Requirements document | What the system must do, in your terms |
| Functional specification | How the system does it |
| Risk assessment | Where failure matters and what controls answer it |
| Test protocols | Installation, operational and performance tests |
| Traceability matrix | Every requirement traced to a test |
| Test summary report | The evidence, summarised for release |
| Release notes and version history | What changed, when, and why |
The acceptance criteria agreed upfront are the same criteria the tests execute. One agreed set serves both commercial acceptance and the quality record.
Questions
Questions a first review asks
Have you run this in a regulated environment before?
No. What exists is a verification pipeline running in production against heterogeneous data arriving from sources nobody controls, described on the company page.
The commercial structure is built around that answer. The configuration for your data types is written during the engagement, every part of it acceptance-tested before it is built, and the first milestone is deliberately small enough that you find out whether it works early rather than at the end.
Do you replace our existing systems?
No. Your systems of record stay the systems of record and your reviewer workflow stays where it is. The modules run inside your environment against your storage, take items as they arrive, and hand back typed outputs with the evidence for every check.
The coverage section above draws that boundary as a diagram. Everything outside the covered segment is yours and does not change.
How do you handle our data format?
As a source like any other. Conduit maps a source into the typed output in code, with a set of checks named in the agreed scope. A new source type is a code change to the field map.
What the module does with a given format today belongs in a technical session with your team rather than in a claim on this page. Ask for one and the answer will be specific.
Why work with a vendor who has no references in our sector?
The structure answers it: fixed scope, fixed fee, acceptance criteria agreed before build, milestone billing. If the software does not meet the criteria it is not accepted and not billed. An established vendor on time and materials is paid whether or not the thing works.
The company page describes where the pipeline already runs in production.
Do you hold SOC 2 or ISO 27001?
No. Neither certification is held, and no report exists to send.
The trust page states every status in plain language, including the negative ones, and what is available instead.
Where does our data go?
Under the preferred deployment, nowhere: the modules run inside your environment, against your storage, under your identity provider. Quantscope holds no client data and initiates no inbound connection.
Where a hosted deployment is required, region, retention and deletion are set in the agreement rather than left to a default.
Can we audit you?
Yes, and before signature rather than after. The right to audit is written into the agreement.
The trust page describes what an audit gets access to and how to schedule one.
Who owns what you build?
You own your configurations, your integrations and any model trained on your data, and you receive a licence to run the modules. Quantscope keeps the underlying platform and tooling.
The split is agreed before work begins, not negotiated after delivery.
What happens if you stop operating?
The answer is contractual rather than reassuring. Documented handover written during the engagement rather than after it, source escrow available as a term, and a scope that ends with software your team runs without us present.
Can you work under our procedures rather than your own?
Yes, and that is the expected arrangement. The software runs under your quality system, with your team holding release.
Acceptance criteria, re-evaluation thresholds and audit trail expectations are written in your terms in the agreement.
Contact
Start with the data
Send the data type, the volume, and what currently has to be checked by hand. If a module cannot be scoped against acceptance criteria, you will be told so.
Request a technical sessiongoes to info@quantscope.ai · response within two business days