Custom Trustpilot Review Management Platform (AI-assisted)
Budget: €250 – €750 EUR
Custom Trustpilot Review Management Platform (AI-assisted)
Background
We operate multiple websites across different markets and receive Trustpilot reviews in several local languages.
We are looking to build a custom, internal web application to centralise review handling, improve response quality, and enable controlled use of AI for drafting and translating replies.
This is not a no-code or Zapier/Make project. We are explicitly looking for a stable, extensible, production-grade solution.
⸻
Project Goal
Build an internal platform that allows our team to:
• Collect Trustpilot reviews from multiple business units
• Draft and approve replies efficiently
• Ensure replies are always published in the correct local language
• Measure reply quality and continuously improve AI output
• Scale to additional markets and features over time
⸻
Key Functional Requirements
1. Trustpilot Integration
• Fetch reviews via the Trustpilot Service Reviews API
• Support multiple Trustpilot business units
• Store reviews locally (database) for history, reporting, and rate-limit safety
• Publish replies via Trustpilot API
• Edit replies by deleting and reposting (supported Trustpilot pattern)
⸻
2. AI-Assisted Reply Workflow
• AI generates draft replies in English only (internal working language)
• Users review, edit, and approve replies in English
• AI translates and localises the final reply into the review’s original language
• Only the local-language version is published publicly
Important:
• No free-form AI chat
• No uncontrolled automation
• AI must be used as a controlled service via API (e.g. OpenAI or Azure OpenAI)
⸻
3. User & Signature Handling
• Internal users approve replies
• Public replies are signed automatically based on market rules
Examples:
• Some markets use “Per – Japebo”
• Others use “Thomas – Japebo”
• Signatures and closing phrases must be configurable per country/market
• Users should not manually type signatures
⸻
4. Dashboard & Metrics
The system must provide a dashboard with at least:
• Number of replies published
• % of replies approved without edits
• Light vs heavy edit ratio
• Average edit time per reply
• Filters by:
• Date range
• Market
• Rating (1–5 stars)
• Trend view over time
These metrics are core to evaluating AI quality.
⸻
5. AI Learning (Non-Training Based)
We do not expect the model itself to retrain automatically.
Instead, the system must:
• Store AI draft vs final approved reply
• Track edit level (none / light / heavy)
• Allow prompt improvements and example-based learning
• Support prompt versioning and comparison
⸻
Technical Expectations
Preferred Stack (open to discussion)
• Backend: Python (FastAPI) or Node.js (NestJS)
• Database: PostgreSQL
• Background jobs: Celery / BullMQ / equivalent
• Frontend: React (admin dashboard)
• AI: OpenAI API or Azure OpenAI
• Hosting: Dockerised, cloud-ready
Non-functional Requirements
• Clean architecture
• Clear separation of concerns
• Good error handling and logging
• Secure handling of API credentials
• Well-documented setup and deployment
⸻
Deliverables
• Backend service with API endpoints
• Admin web interface
• Database schema and migrations
• Trustpilot + AI integration
• Dashboard with metrics
• Basic documentation (setup, config, architecture)
⸻
Project Scope & Phasing
We expect this to be built in phases:
Phase 1 (MVP)
• Review ingestion
• AI draft generation
• Manual approval
• Local-language publishing
• Core metrics
Phase 2 (optional / later)
• Partial automation rules
• Advanced analytics
• Multi-platform review support
⸻
Ideal Freelancer Profile
• Strong backend experience
• Comfortable integrating third-party APIs
• Experience with AI APIs (OpenAI or similar)
• Able to think in systems and workflows, not just endpoints
• Comfortable working independently with clear requirements
• Experience building internal tools or admin platforms is a strong plus
⸻
What to Include in Your Proposal
Please include:
• Relevant past projects (especially API-heavy or AI-assisted systems)
• Preferred tech stack and rationale
• Estimated timeline for MVP
• Any assumptions or risks you see
• Availability for ongoing improvements after MVP
⸻
Important Notes
• This is a long-term internal system, not a quick prototype
• Code quality and maintainability matter
• We value thoughtful architecture over speed alone
Background
We operate multiple websites across different markets and receive Trustpilot reviews in several local languages.
We are looking to build a custom, internal web application to centralise review handling, improve response quality, and enable controlled use of AI for drafting and translating replies.
This is not a no-code or Zapier/Make project. We are explicitly looking for a stable, extensible, production-grade solution.
⸻
Project Goal
Build an internal platform that allows our team to:
• Collect Trustpilot reviews from multiple business units
• Draft and approve replies efficiently
• Ensure replies are always published in the correct local language
• Measure reply quality and continuously improve AI output
• Scale to additional markets and features over time
⸻
Key Functional Requirements
1. Trustpilot Integration
• Fetch reviews via the Trustpilot Service Reviews API
• Support multiple Trustpilot business units
• Store reviews locally (database) for history, reporting, and rate-limit safety
• Publish replies via Trustpilot API
• Edit replies by deleting and reposting (supported Trustpilot pattern)
⸻
2. AI-Assisted Reply Workflow
• AI generates draft replies in English only (internal working language)
• Users review, edit, and approve replies in English
• AI translates and localises the final reply into the review’s original language
• Only the local-language version is published publicly
Important:
• No free-form AI chat
• No uncontrolled automation
• AI must be used as a controlled service via API (e.g. OpenAI or Azure OpenAI)
⸻
3. User & Signature Handling
• Internal users approve replies
• Public replies are signed automatically based on market rules
Examples:
• Some markets use “Per – Japebo”
• Others use “Thomas – Japebo”
• Signatures and closing phrases must be configurable per country/market
• Users should not manually type signatures
⸻
4. Dashboard & Metrics
The system must provide a dashboard with at least:
• Number of replies published
• % of replies approved without edits
• Light vs heavy edit ratio
• Average edit time per reply
• Filters by:
• Date range
• Market
• Rating (1–5 stars)
• Trend view over time
These metrics are core to evaluating AI quality.
⸻
5. AI Learning (Non-Training Based)
We do not expect the model itself to retrain automatically.
Instead, the system must:
• Store AI draft vs final approved reply
• Track edit level (none / light / heavy)
• Allow prompt improvements and example-based learning
• Support prompt versioning and comparison
⸻
Technical Expectations
Preferred Stack (open to discussion)
• Backend: Python (FastAPI) or Node.js (NestJS)
• Database: PostgreSQL
• Background jobs: Celery / BullMQ / equivalent
• Frontend: React (admin dashboard)
• AI: OpenAI API or Azure OpenAI
• Hosting: Dockerised, cloud-ready
Non-functional Requirements
• Clean architecture
• Clear separation of concerns
• Good error handling and logging
• Secure handling of API credentials
• Well-documented setup and deployment
⸻
Deliverables
• Backend service with API endpoints
• Admin web interface
• Database schema and migrations
• Trustpilot + AI integration
• Dashboard with metrics
• Basic documentation (setup, config, architecture)
⸻
Project Scope & Phasing
We expect this to be built in phases:
Phase 1 (MVP)
• Review ingestion
• AI draft generation
• Manual approval
• Local-language publishing
• Core metrics
Phase 2 (optional / later)
• Partial automation rules
• Advanced analytics
• Multi-platform review support
⸻
Ideal Freelancer Profile
• Strong backend experience
• Comfortable integrating third-party APIs
• Experience with AI APIs (OpenAI or similar)
• Able to think in systems and workflows, not just endpoints
• Comfortable working independently with clear requirements
• Experience building internal tools or admin platforms is a strong plus
⸻
What to Include in Your Proposal
Please include:
• Relevant past projects (especially API-heavy or AI-assisted systems)
• Preferred tech stack and rationale
• Estimated timeline for MVP
• Any assumptions or risks you see
• Availability for ongoing improvements after MVP
⸻
Important Notes
• This is a long-term internal system, not a quick prototype
• Code quality and maintainability matter
• We value thoughtful architecture over speed alone