fleak-ai-workflows
Fleak is a data-infrastructure platform that normalizes, filters, governs, and delivers real-time data to AI applications and downstream systems, using AI-orchestrated, self-healing pipelines to reduce noise, costs, and manual maintenance for enterprise use cases.
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Quick Overview
Best for: Automation
What it does
Automation software for decision-makers comparing workflow fit and alternatives.
Best fit
Automation
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fleak-ai-workflows
Fleak is positioned as an AI infrastructure layer between raw data sources and AI applications or downstream systems. It normalizes, filters, governs, and delivers data in real time, aiming to reduce noise and schema-related failures that degrade AI and detection systems. The platform targets enterprise verticals that require reliable, governed data flows such as cybersecurity (SOC/SIEM), Industrial/OT, aviation & logistics, and financial services, and advertises capabilities like self-healing pipelines, value-aware routing, and fine-grained data governance.
Fleak simplifies AI workflows for data teams with a serverless API builder and integrations.
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Claim this listing for $29Key Features
Value-aware routing
Fleak's AI evaluates incoming data points against downstream application needs and routes data accordingly (real-time value moves fast, compliance value to long-term storage, no-value is dropped).
AI-orchestrated, self-healing pipelines
Detects schema changes, generates new configs, and redeploys automatically with human review optional; average self-heal time stated as 3 minutes.
Schema normalization and mapping
Normalizes any source and schema into the desired schema (examples: OCSF, UDM, CSF) in real time and claims auto-generated mappings within minutes.
Filtering and deduplication
Filters and deduplicates events at ingestion to reduce storage needs and noise before data reaches SIEMs or data lakes.
LLM token and cost optimization
Claims up to 40% token reduction for AI agents by providing normalized, deduplicated inputs to downstream LLM-powered tools.
Governed delivery & fine-grained access control
Enforces fine-grained access control at the data layer, logs every transformation, and provides a full audit trail.
Wide integrations
Connects to many enterprise sources without custom connectors and lists 50+ integrations, including OT, SIEM, cloud, and APIs.
Natural-language copilot for orchestration
Use natural language to describe desired outcomes and the platform's copilot will build the pipeline or configuration in minutes.
Real-time delivery with zero storage required
Delivers clean, governed data to destinations in real time and advertises "zero storage required" for real-time flows.
Pricing
Current pricing details are not available from the vendor source.
Use Cases
Cybersecurity / SOC / SIEM
Normalize and deduplicate logs to OCSF/UDM/CSF, filter noise before it reaches detection tools, reduce alert fatigue, and enforce per-tool governance and audit trails for SOC workflows.
Industrial / OT
Normalize OT and IoT telemetry to a unified schema, deduplicate sensor noise before it reaches analytics and data lakes, and enforce access controls with full auditability for manufacturing and energy operations.
Aviation & Logistics
Ingest and normalize telemetry and operational feeds (e.g., ACARS) to improve cargo, MRP, and operations data quality for downstream systems.
Financial Services / Compliance & Fraud
Normalize transaction data across sources, deduplicate and enrich events for fraud and compliance systems, and provide a regulatory audit trail and fine-grained governance.
Integrations
OSIsoft PI
Industrial / OT integration for telemetry and process historian data (listed under platform integrations).
Splunk
Cybersecurity / SIEM integration to normalize and route events before they reach Splunk.
Ignition SCADA
Industrial / OT SCADA integration for OT telemetry normalization.
Palo Alto XSIAM
Cybersecurity integration example for delivering governed telemetry into detection tools.
ACARS
Aviation & Logistics feed example for operational data ingestion.
Microsoft Sentinel
SIEM integration to normalize and filter data before delivery to Sentinel.
Benefits
Limitations
No verified limitations are available.
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Step 1: Connect any source — cloud, OT, endpoints, APIs, databases (the site states no custom connectors required).
- 2 Step 2: Orchestrate with AI — describe desired outcomes in natural language and use Fleak's copilot to build the pipeline.
- 3 Step 3: Transform your data — identify event types, branch by destination intent, and normalize to the chosen schema; Fleak updates automatically on schema changes.
- 4 Step 4: Deliver anywhere — send clean, governed data in the specified schema to AI applications, data lakes, SIEMs, or other destinations in real time.
Support
Primary contact email provided on the site: [email protected]
demo
Book a demo / Book a 30 minute demo options are listed on the site.
docs
Documentation link referenced in the footer ("Documentation").
API
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