Preparing for Integration
🛠️ Preparing for Integration
Before any technical integration can begin, Fyre requires a short preparation phase.
This phase ensures:
✅ Data can be processed correctly from the start
⚡ Integration can scale smoothly once production data is enabled
🔒 Shared understanding of data scope, quality, and privacy safeguards
The preparation phase always follows the same sequence and applies to all integration models.
🔄 Required Integration Flow
Integration with Fyre follows this exact order:
Share the list of outlets
Provide one month of transactional data for those outlets
Request API access or confirm the final data delivery method
This sequence applies to API-based delivery, file-based delivery, and reverse integration. Following this order ensures:
Correct anonymization configuration
High data quality
Minimal rework later
1️⃣ Step 1: Send the List of Outlets
Sharing a complete list of outlets upfront allows Fyre to prepare the integration in a controlled and privacy-safe way.
The outlet list is used to:
🆔 Create internal identifiers and mappings
🔒 Configure anonymization and privacy safeguards
🌍 Validate geographic and market coverage
⚙️ Prepare ingestion, monitoring, and validation pipelines
Outlet Eligibility Assessment
Once the list is received, Fyre evaluates each outlet to ensure it aligns with Fyre’s scope and analytical models:
🏠 Away-From-Home relevance – must belong to AFH segment
📊 Historical data availability – at least 12 months for trends, year-over-year comparisons, and seasonality correction
📅 Indicators like first/last order dates help identify active, new, or inactive outlets early
Feedback Shared with the Partner
Fyre provides structured feedback to increase transparency:
🌎 Coverage across regions
📊 Coverage across market segments
🏷️ Distribution of outlet types
🔍 High-level insights into the partner’s client base
This helps partners understand how their network maps into Fyre’s analytical framework before moving forward.
For detailed field requirements, see: Outlet List Requirements
2️⃣ Step 2: Send One Month of Transactional Data
Once the outlet list is shared, provide ≈1 month of transactional data for the same outlets.
Purpose: validation, alignment, and enrichment.
The sample data allows Fyre to:
✅ Validate data structure and consistency
🛠️ Test product classification and enrichment logic
📊 Assess overall data quality
⚠️ Identify potential issues early, before production ingestion
For detailed field requirements, see: Transactional Data Requirements
3️⃣ Step 3: Request API Access or Confirm Delivery Method
After reviewing the outlet list and sample data:
🔑 Request API access for API-based delivery, or
📁 Confirm an alternative data delivery method
Once done, historical data delivery and ongoing daily production flows can start according to the agreed setup.
🔒 Data Confidentiality, Anonymization, and Transparency
Fyre ensures confidentiality, security, and anonymity of all outlet-level data.
Principles:
🛡️ Outlet identities are never disclosed or commercialized
🔒 Raw/identifiable data is never shared externally
📊 All outputs are anonymized and aggregated, compliant with data regulations
📝 Internal access is strictly controlled, logged, and limited
Some internal processing may reference menu descriptions or product naming conventions to classify products accurately, but it is strictly for technical and analytical purposes.
Transparency, trust, and data integrity are core to Fyre’s approach. Further details are available in contractual or technical documentation if needed.
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