ExpertiseData Engineering & AutomationCollection & ingestion
Business solution

Collection & ingestion

Connect all sources—applications, APIs, IoT, files, databases, and streams—without imposing a single format. We design reliable, observable, and scalable ingestion that absorbs heterogeneity at the entry point. The goal: keep the data pipeline fed continuously, even when producers change pace or protocol.

Key commitments
  • Multi-protocol connectors
  • Real-time and batch ingestion
  • Edge gateway and cloud
  • Controlled recovery and buffering
In plain terms

Absorb heterogeneity without being constrained by it.

We build connectors that can absorb structured, semi-structured, or unstructured data: business applications, APIs, industrial equipment, embedded systems, sensors, logs, messages, files, geospatial streams, audio, image, or video.

Ingestion is designed to hold in production: buffering, recovery, rate control, observability and producer decoupling. Each source is treated as an exchange contract, with schemas, technical SLAs and explicit recovery mechanisms.

On sites with intermittent connectivity, we favor edge gateways that can buffer, compress and resync without loss. Cloud, private and on-prem coexist based on sovereignty and latency.

The expected outcome is not a catalog of isolated connectors, but an industrialized, documented and monitored intake layer, ready to feed quality, processing and fusion.

MultiSupported protocols
RT / BatchIngestion modes
EdgeIntermittent sites
DLQControlled recovery
What we do

Bring all your sources into the flow.

Ingestion building blocks tailored to each source’s protocol, volume and criticality.

Application connectors

REST, GraphQL, WebSocket, SFTP, and partner / SaaS exchanges. We standardize authentication, versioning, and retries so every API remains a reliable producer.

En clair : Your applications feed the chain without fragile manual scripts.
API GatewayOAuth / mTLS

IoT & field

MQTT, telemetry, edge gateways, and industrial protocols. We handle event density, sensor noise, and network outages without saturating the platform core.

En clair : The field becomes a continuous source, even when temporarily offline.
MQTTEdge gateway

Databases & files

SQL, NoSQL, CSV, JSON, periodic exports, and synchronizations. Batch extractions coexist with CDC to limit load on source systems.

En clair : We reuse what already exists, without rewriting everything.
CDC

External flows

Open data, geospatial, partners, and real-time sources. We define exchange contracts, formats, and responsibilities if a feed breaks.

En clair : External data enrich context without becoming a single point of failure.

Streaming

Kafka and brokers for continuous high-volume events. Partitioning, retention and decoupled consumers absorb peaks.

En clair : The stream arrives continuously, ready for processing and fusion.
Kafka

Ingestion resilience

Local buffer, retry, dead-letter and connector monitoring. Every failure is classified, replayable and visible to operations.

En clair : An outage does not erase data: it resumes cleanly.
Frequently asked questions

Collection & ingestion — key questions.

Can you take over existing connectors?
Yes. We map the current estate, assess reliability and maintainability, then consolidate what is solid. The rest is industrialized with common standards (observability, retries, schemas) to avoid a script jungle.
Do you manage sites with intermittent connectivity?
Yes. Edge buffering, sync resume, compression, and backup links keep collection going even when the network is degraded. The central platform then catches up without destructive duplicates.
What volumes can you absorb?
From daily batch to high-frequency streaming. Sizing follows the business need, target latency and architecture (broker, partitioning, storage). We also calibrate observability and retention costs.
Do we need to migrate everything to streaming?
No. Many sources remain best as batch or CDC. We choose the mode per source to avoid needlessly complicating operations.
How do you secure exchanges?
Depending on context: mTLS, OAuth, VPN, encryption at rest and in transit, network isolation, and access logging. Secrets are externalized and rotatable.
Data Engineering & Automation

Sources to connect to your data platform?

List your systems, protocols, and constraints (latency, sovereignty, intermittence): we propose a realistic, prioritized ingestion plan.