Preparing for Integration

Before any technical integration can begin, Fyre requires a short preparation phase.

This phase ensures that data can be processed correctly from the start and that the integration can scale smoothly once production data is enabled. It also establishes a shared understanding of data scope, quality, and privacy safeguards before any ongoing data flows are activated.

The preparation phase always follows the same sequence and applies to all integration models.

Required integration flow

Integration with Fyre always follows this order:

1. Share the list of outlets

2. Share one month of transactional data for those outlets

3. 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 allows Fyre to configure anonymization, validate data quality, and avoid rework later in the integration.

Step 1: Send the list of outlets

The first step is sharing a complete list of outlets.

Providing the outlet list upfront allows Fyre to prepare the integration in a controlled and privacy-safe way. The list is used to create internal identifiers, configure anonymization rules, and validate geographic and market coverage before any transactional data is processed.

Specifically, the outlet list enables Fyre to:

• Create internal identifiers and mappings

• Configure anonymization and privacy safeguards

• Validate geographic and market coverage

• Prepare ingestion, monitoring, and validation pipelines

In addition to technical preparation, the outlet list allows Fyre to perform an early eligibility assessment of the partner’s network. This helps ensure that the integration focuses on outlets that are relevant within Fyre’s ecosystem and suitable for analytics and monetization use cases.

For detailed field requirements, see: Outlet List Requirements

Outlet eligibility assessment

Once the outlet list is received, each outlet is evaluated against a set of criteria to ensure it aligns with Fyre’s scope and analytical models.

This assessment includes:

Away-From-Home relevance Outlets must belong to the AFH (Away-From-Home) segment and align with Fyre’s customer strategy.

Historical data availability For meaningful analysis, outlets are expected to have sufficient historical data. At least 12 months of data is required for year-over-year (N-1) comparisons, trend analysis, and seasonality correction.

When available, indicators such as first and last order dates help identify active, new, or inactive outlets early in the process.

Feedback shared with the partner

After processing the outlet list, Fyre can share structured feedback with the partner to increase transparency and alignment.

This may include:

• Coverage across regions

• Coverage across market segments

• Distribution of outlet types

• High-level insights into the partner’s client base

This feedback helps partners better understand how their network maps into Fyre’s analytical framework before moving forward.

Step 2: Send one month of transactional data

Once the outlet list is shared, the next step is providing approximately one month of transactional data for those same outlets.

This data is used strictly for validation, alignment, and enrichment purposes. It allows Fyre to confirm that transactional data can be interpreted consistently and mapped correctly to the previously shared outlets.

The sample data is used 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

Step 3: Request API access or confirm delivery method

After the outlet list and sample transactional data have been reviewed and approved, the final integration setup can be confirmed.

At this stage:

• API access can be requested for API-based delivery, or

• An alternative data delivery method can be finalized

Once this step is completed, historical data delivery and ongoing daily production data flows can be enabled according to the agreed setup.

Data confidentiality, anonymization, and transparency

Fyre is fully committed to the confidentiality, security, and anonymity of all outlet-level data shared on the platform.

All data exposed through Fyre products and dashboards is strictly aggregated and anonymized. At no point are individual outlets, transactions, or outlet lists identifiable by third parties.

To ensure high-quality market segmentation and accurate product classification, Fyre may temporarily process certain non-aggregated elements internally. This processing is strictly limited to technical and analytical purposes and is never exposed externally.

For example, some products such as signature cocktails or house recipes cannot be reliably classified without referencing menu descriptions or product naming conventions. In these cases, limited internal access is required solely to interpret and standardize the data correctly.

The following principles always apply:

• Outlet identities are never disclosed or commercialized

• Raw or identifiable data is never shared externally

• All outputs are anonymized, aggregated, and compliant with applicable data protection regulations

• Internal access is strictly controlled, logged, and limited to defined purposes

Transparency, trust, and data integrity are core to Fyre’s approach. If needed, these safeguards can be further detailed in contractual or technical documentation.