Hashlogics
Case study · Home Services Marketplace · Australia

WorkMateAI

Safe payments and fair disputes for every home-service job.

Disputes, payments, and compliance for Australia's on-demand trades.

Key takeaways

4 things that decide this

  1. 01Hashlogics built WorkMateAI's trust-and-safety system, which handles contracts, held payments, and disputes for Australia's trades marketplace.
  2. 02Payments run through Stripe Connect on a hold-and-release model, freeze on dispute, and generate chargeback evidence.
  3. 03A three-layer agreement model covers platform terms at signup, a provider agreement at onboarding, and a contract per accepted job.
  4. 04Providers are verified against ABN, trade licenses, and insurance before they accept work.
Client
WorkMateAI
Industry
Home Services Marketplace
Region
Australia
Engagement
Marketplace · commissions + platform fees · Trust, safety & payments platform
Overview

WorkMateAI connects customers with verified tradies for home repairs and upgrades. As it grew, payments, contracts, and disputes created real legal risk. We built a structured trust-and-safety system: clear legal agreements, held payments, provider checks, and a phased dispute process. The platform is now legally protected and easier to run.

The challenge

Where the platform carried the risk.

01

The platform had no control over payments or chargebacks.

02

There was no legal contract framework between the parties.

03

Dispute handling was manual and undefined.

04

Tradie verification was weak: licenses, insurance, and identity went unchecked.

05

Messaging language could imply the platform was liable.

06

Payments happened off-platform, with no document generation and limited admin tooling.

What success needed to look like

  • Payments stay inside the platform, with disputes and chargebacks handled instead of absorbed as risk.
  • Every job is backed by a clear legal agreement, not informal messaging that could imply liability.
  • Tradies are verified on license, insurance, and identity before they can accept a job.
  • Disputes follow a defined process the platform can defend, not ad hoc handling.
Our approach

How we delivered it.

  1. 01

    Diagnose

    Reviewed where payments, messaging, and disputes exposed the platform to legal and money risk. Unverified tradies and liability wording in messages topped the list.

  2. 02

    Design

    Designed a three-layer legal agreement model: platform terms, provider agreement, per-job contract. A phased dispute plan starts manual, then adds rules and AI help.

  3. 03

    Build

    Built hold-and-release payments on Stripe Connect, with dispute freezes and chargeback evidence. Contracts are e-signed via DocuSign or HelloSign. Providers are checked against ABN, trade licenses, and insurance. Documents live on AWS S3.

  4. 04

    Launch

    Rolled out the admin case dashboard with automated timers and alerts, next to the new payment and vetting flows. It replaced an off-platform process with no rules.

  5. 05

    Run

    Kept the dispute framework in its manual-to-rule-based phase. The system is built to add an AI resolution agent as case volume grows.

The solution

What we built.

We designed a structured, compliant dispute and payments system that sets clear legal limits. A three-layer agreement model covers platform terms at signup, a provider agreement at onboarding, and a job contract per accepted quote. All carry version history. Payments run through Stripe Connect on a hold-and-release model, freeze on dispute, and generate chargeback evidence. Providers are verified before they accept work. The dispute process runs in phases: manual first, then rule-based, with AI help on the roadmap.

How a dispute moves through the systemLive
  1. Job acceptedPer-job contract e-signed, payment held via Stripe Connect.
  2. Dispute filedPayment freezes; evidence locker opens for both parties.
  3. Manual reviewAdmin dashboard timers and alerts drive the case to a decision.
  4. Rule-based triageRepeat patterns route by rule instead of a fresh manual read.
  5. ResolutionRelease, refund, or chargeback evidence generated automatically.

AI-assisted triage is the next phase, added as case volume grows.

Phased dispute management: manual, then rule-based, with AI-assisted resolution planned
Three-layer legal agreement model with version history
Stripe Connect hold-and-release payments with dispute freeze
Chargeback evidence generation
Provider verification — ABN validation, trade license, insurance, and identity checks
E-signature document generation
Dispute submission with an evidence locker
Admin case dashboard with automated timers and notifications
WorkMateAI tradesperson dashboard with recommended jobs and match scores
WorkMateAI job feed with location and AI match score per job
How it’s built

Tech stack

  • Stripe Connect
  • AWS S3
  • DocuSign / HelloSign

Integrations

  • Stripe Connect (hold-and-release payments + identity)
  • DocuSign / HelloSign (e-signature)
  • AWS S3 (secure document storage)

Security

  • Encrypted storage for legal files
  • Role-based admin access
  • Audit logging for all dispute actions
  • Clear data-retention policies
More from the build
WorkMateAI analytics with job performance trends and category breakdown
WorkMateAI AI ad studio for generating tradesperson service ads
WorkMateAI applicant detail view for a posted job
The takeaway

A marketplace's legal exposure shows up when something goes wrong. Building the dispute and payment framework first is what makes growth defensible. Resisting AI resolution on day one was the harder call. A pattern needs a human review before it becomes a rule. A rule earns automation only once it holds up.

By Abdul Basit, CEO, HashlogicsUpdated
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  1. 01

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  2. 02

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  3. 03

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Abdul Basit, CEO of Hashlogics

“I started Hashlogics because too many teams ship a demo, get paid, and disappear. We build to a standard we’d run ourselves — and we stay to keep it running.”

Abdul Basit · CEO · a direct line

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