Zyfrr

Data and APIs

Clean data, and integrations that hold,under real conditions.

Custom APIs, third party integrations and reporting you can act on, built on a data model everyone agreed before the code.

The problem

Why do integrations keep breaking?

Because they get built before anyone decides which system owns which fact, so every change starts an argument.

How it usually goes

  • Integrations built before anyone agreed the data model
  • Scripts that break whenever a vendor changes an endpoint
  • Two systems both claiming to own the same record
  • Reports assembled by hand every Friday
  • A failed sync that stays silent until month end
  • A retry that quietly charges the customer twice

How we do it

  • The data model and its ownership agreed first
  • Retries, timeouts and writes that cannot double apply
  • One system owns each fact, by decision not accident
  • Reporting refreshed from the source automatically
  • Alerting the moment a sync falls behind
  • A reconciliation view that proves the two sides match

How it works

Many systems, one model, many consumers

The order matters. Agree what a customer is and which system owns each fact first, and the integrations become straightforward. Skip it and you get scripts that break whenever a vendor changes an endpoint.

  1. 01

    Systems

    • CRM, accounts, ops
    • Whatever you already run
  2. 02

    Ingest

    • Scheduled and webhook
    • Retries on failure
  3. 03

    One model

    • Agreed ownership
    • Built to outlast tools
  4. 04

    API layer

    • Documented, versioned
    • Least privilege access
  5. 05

    Consumers

    • Apps and dashboards
    • Partners and reports
  6. Retry and reconcile, back to Ingest

Data and APIs

What we build

01

Custom APIs

A documented, versioned, secure interface to your own data, so your apps, partners and internal tools all read from one place.

02

Third party integrations

Payment gateways, accounting software, CRMs, logistics providers and messaging platforms, connected with the retry and failure handling that keeps records straight.

03

Data models that survive growth

Designed for the questions you will need to answer in three years, not only the screens you need next month.

04

Reporting and dashboards

The numbers that decide something, pulled from the source and refreshed automatically, so nobody assembles them by hand.

05

Migrations between systems

Moving data out of a tool you are leaving, with the mapping, cleaning and verification that stops history being quietly lost.

06

Legacy database rescue

Databases that grew without a plan and now block every change. Restructured carefully, with the application still running throughout.

Two systems can only agree once you have decided which one owns the truth.

As standard

In every integration

  • 01Documented endpoints with versioning
  • 02Authentication and least privilege access
  • 03Retries, timeouts and idempotent writes
  • 04Alerting when a sync fails or falls behind
  • 05A reconciliation view, so you can prove the data matches
  • 06Everything running in infrastructure you own

The timeline

What a typical integration looks like

The mapping and cleaning is usually the largest part, and it decides whether anyone trusts the numbers afterwards.

  1. Week 1

    Map the systems

    What holds what, what is copied by hand, and where records already disagree.

  2. Week 2

    Agree the model

    What a customer is, and which system owns each fact. Everything rests on this.

  3. Weeks 3 to 5

    Build the layer

    Documented endpoints, scheduled and webhook ingest, alerting when a sync lags.

  4. Week 6

    Reconcile and prove

    A view showing both sides match, so trust is demonstrated rather than claimed.

  5. Ongoing

    Watch the seams

    Vendors change APIs. Alerts catch it, and the contract lives in one place.

Questions

Questions about data and integration work

Usually yes. Most business software exposes an API, and where one does not there are almost always exports, webhooks or a database we can read. What matters more is deciding which system owns each piece of data, because without that a two way sync will fight itself.

It will do both eventually, so the integration is built expecting it. Failed calls retry with backoff, writes are idempotent so a retry cannot double charge or duplicate a record, and a sync that falls behind raises an alert rather than silently drifting.

No. Cleaning and reconciling it is part of the work and usually the largest part. Waiting until the data is tidy before starting is the reason these projects never begin.

Yes, and it is a common request. We generally put a designed interface in front of the database rather than exposing tables directly, so the schema can change later without breaking every consumer.