Pi.One takes over the collection, preparation and processing of data from all consumer systems
- 01
Collects information from heterogeneous sources
Batch and streaming ingestion from file systems, object stores, APIs, message brokers and network interfaces — a single entry point for enterprise and telecom data.
- Local Disk, FTP/SFTP/SCP, S3/Hadoop connectors, Kafka, MQTT, JMS, MSMQ
- REST/SOAP, HTTP/WebSocket, TCP/UDP
- File/S3 Collector & Forwarder, Mail Sender, Telegram Bot Collector/Sender
- 02
Checks data integrity and brings it to a single format for internal processing
Data model definitions, inbound validation and record preparation for batch and real-time pipelines.
- Universal Data Description Format (UDD)
- Integrity checks and data-quality profiles
- Connection profiles, audit and traceability
- 03
Transforms data according to business logic
Visual and programmatic chains: decode, route, session handling and custom scenarios on Pi.Lang and Groovy.
- Decoder, Encoder, Groovy, Record Router, Session
- Aggregation, correlation, merge, duplicate detection
- Archiving and compression
- 04
Generates and delivers output data in a given format
Batch and operational delivery to billing, CRM, warehouses, analytics and external APIs with controlled hand-off.
- Encoding to consumer-specific formats
- Schedules, events and delivery subscriptions
- Pipeline and SLA monitoring
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Architecture, typical scenarios and Pi.One integration scope
Data flows and processing (Mediation)
Example chain: sources → decode → validation → business logic → delivery to downstream systems.
Table 1: Core & Batch integration scope
| Business tasks | Available options | Typical outcomes |
|---|---|---|
| Collection and delivery of files, objects and messages | Local Disk/FTP/SFTP/SCP, S3/Hadoop connectors, File Collector, File Forwarder, S3 Collector, S3 Forwarder, Mail Sender, Telegram Bot Collector, Telegram Bot Sender | Batch loading and controlled delivery via file systems, object storage and external communication channels. |
| Data conversion and custom transformation | Decoder, Encoder, Groovy, Record Router, Session, archiving and compression, aggregation/correlation/merge, duplicate detection | Pi.Lang-based decode/encode, custom processing, routing, session aggregation and data quality control in end-to-end batch flows. |
| Data access and storage integration | DB and SQL connectors, connection profiles, data audit and operational storage options | Batch upload/download, enrichment and corporate data lifecycle processes. |
Pi.One Real-time
Table 2: Real-time integration scope
| Business tasks | Available options | Typical outcomes |
|---|---|---|
| API and event-driven service integration | REST, SOAP, HTTP and WebSocket integration patterns with HTTP Server, REST Router and orchestration agents | Real-time API exposure, schedule/event-driven runs and runtime orchestration of workflows. |
| Messaging and streaming | JMS, Kafka, MSMQ and MQTT integration patterns, including Kafka Consumer, Kafka Producer and MQTT Collector | Streaming ingest and event distribution for low-latency pipelines. |
| Network and socket integrations | TCP/IP and UDP integration patterns, protocol-level routing and event-driven handling | System-to-system interaction and control processes in near real-time. |
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