Data Fabric for
Modern Autonomous Operations
Unlock the full potential of your IT data with our Data Fabric, designed to ingest, enrich, transform, and route data at scale across any stack and environment.
2000+ Data Bot Library
Automate data processing activities using pre-built bots that perform API operations, data operations – like filtering, aggregating, enriching or routing data. Automate ML model training or inferencing. Bots work together – to help you implement telemetry and observability pipelines.
Bots automate API requests, data operations and tasks
2000+ bots in the library; build new ones with the SDK
Bots combine in low-code pipelines for any use case
Out-of-the-box telemetry and observability pipelines
Pipelines authored in a Jupyter-style studio
Bots run distributed to enable edge analytics
ML training, inferencing and Gen AI bots for LLMs
Low-code bots, Ops and citizen-developer friendly
Universal MCP Server
Universal Connectivity & Tooling
Unleash your agents.
Fabrix.ai plugs into your observability, ITSM, cloud, infrastructure, and container stacks out of the box. The Universal MCP Server connects every source in real-time - running federated agents without data duplication.
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Telemetry Pipelines
Craft your data flow with low-code or pre-built packs. Deploy on-prem, cloud or hybrid. Author pipelines in the AIOps studio.
- Routing decouples data producers from consumers
- Convert to OpenTelemetry for any OTEL backend
- Rich pipeline set for telemetry and observability
- In-memory pipelines for inline high throughput
- Inference pipelines for anomaly detection
- Event-driven pipelines for change detection
- Always-on service and scheduled timed pipelines
- Action pipelines for automations, alerting for ticketing
Universal Ingest
Real-time data ingestion of IT operations/service management data from devices, element managers, domain managers, object stores and data lakes. Route raw data, transformed data or compressed data to other object stores or data lakes
- Ingest many data types
- MELT, incidents, tickets, CMDB and topology
- Convert to OpenTelemetry for any OTEL backend
- Agentless approach to data ingestion
- Sources and targets: devices, apps, lakes, APIs
- Modes: sync, async, push/pull, streaming, batch
- Protocols: SNMP, API, OTEL, Netconf/Yang, gNMI
Pipeline Studio
A citizen-developer-friendly, Jupyter-style notebook for authoring, testing and debugging pipelines before publishing to production. Installs on any VM, workstation or laptop.
- Build Data Pipelines using No-Code / Low-Code interface with 2000+ bots
- Flexible Data Integration & Preparation
- Manage Pipeline Lifecycle
Data Discovery & Enrichment
Automatically build a Full-stack application dependency map (ADM) - agentless, no CMDB - and enrich data with business context.
- Automatically builds Full-stack application dependency map
- Agentless discovery approach. No dependency on CMDB
- Near real-time updates: event-driven, periodic polling or on-demand
- Enriches raw event/alert data with app/business context
- Utilize enrichment responses from third-party tools, including threat intelligence feeds (e.g., MTTRE attack), Geo IP lookups, bad IP lookups, and knowledge store queries
Liberate Data & Reduce Costs with Data Routing
- Liberate data by separating data producers and consumers
- Route to multiple locations - Cisco Observability Platform, Fabrix.ai AIOps Platform, Data Lakes, Data Lakehouse like Dynatrace Grail, Splunk, Log Stores, Analytics Platforms and Composable Dashboards
Composable Pipelines with Low-Code Bots
- Craft your perfect data flow with low-code or use pre-built solutions
- 2000+ bots in the library. Easily build new bots with SDK
- Deploy freedom: on-prem, cloud or hybrid environments.
Pipeline Choice: In-Memory, Inferencing, Event-Driven, etc.
- Rich pipeline set for many use case scenarios
- In-memory pipelines for inline high throughput
- Inference pipelines for anomaly detection
- Event-driven pipelines for change detection
- Always-on service and scheduled timed pipelines
- Action pipelines for automations, alerting for ticketing
Analyst Endorsed
- Gartner recently recognized Fabrix.ai Data Observability pipelines as a trusted vendor with Telemetry pipeline offering
Frequently
asked questions
The Fabrix.ai Data Fabric unifies all data sources, structured and unstructured, in real time. It is designed to ingest, enrich, transform, and route data at scale across any stack and environment, providing the unified data foundation for modern autonomous IT operations.
The Data Bot Library provides 2000+ pre-built bots that automate data processing activities such as API operations and data operations like filtering, aggregating, enriching, or routing data. Bots can automate ML model training or inferencing, include Gen AI bots to interact with LLMs, and work together in low-code pipelines to implement telemetry and observability use cases. New bots are easy to develop with the SDK, and bots can run and communicate in distributed environments to enable edge analytics.
Telemetry Pipelines let you craft your data flow with low-code tooling or pre-built solution packs, and deploy on-prem, in the cloud, or in hybrid environments. They support many-to-many routing that separates data producers and consumers, conversion to Open Telemetry for any OTEL backend, in-memory pipelines for high-throughput inline processing, inference pipelines for anomaly detection and classification, event-driven pipelines for topology updates and change detection, service and scheduled pipelines for ingestion, and action and alerting pipelines for automations and ticketing.
Universal Ingest performs real-time data ingestion of IT operations and service management data from devices, element managers, domain managers, object stores, and data lakes. It uses an agentless approach and ingests many data types including incidents, MELT (Metrics, Events, Logs, Traces), KPIs, asset inventory/CMDB, topology, and tickets. It supports synchronous, asynchronous, push/pull, streaming, and bulk/batch modes, and protocols including SNMP, API, Open Telemetry, Netconf/Yang, Bulkstats, gNMI, Splunk forwarders, and HEC.
Pipeline Studio is a citizen-developer-friendly, Jupyter-style notebook environment for authoring, testing, debugging, and inspecting pipelines before publishing to production. It lets you build data pipelines using a no-code/low-code interface with 2000+ bots, supports flexible data integration and preparation, and manages the full pipeline lifecycle. It can be installed on any VM or even on developer workstations and laptops.
Data Discovery & Enrichment automatically builds a full-stack application dependency map (ADM), capturing physical and logical topologies through an agentless discovery process with no dependency on CMDB. It provides near real-time updates via event-driven, periodic polling, or on-demand methods, and enriches raw event and alert data with application and business context. It can also use enrichment responses from third-party tools, including threat intelligence feeds, Geo IP lookups, bad IP lookups, and knowledge store queries.
The Data Fabric liberates data by separating data producers from consumers, allowing you to route data to multiple destinations including the Cisco Observability Platform, the Fabrix.ai AIOps Platform, data lakes, data lakehouses such as Dynatrace Grail, Splunk, log stores, analytics platforms, and composable dashboards. This routing flexibility helps reduce data and storage costs.
Yes. Gartner recognized Fabrix.ai data observability pipelines as a trusted vendor with a telemetry pipeline offering, and the platform's out-of-the-box telemetry and observability pipelines are Gartner recognized.