PipeSmith detects failures in milliseconds, diagnoses root causes with AI, and remediates automatically—reducing manual intervention from 75 minutes to 15 seconds.350x faster resolution. 90%+ autonomous healing. Zero firefighting.
Stop firefighting. Start building. PipeSmith delivers measurable ROI from day one with autonomous failure detection, diagnosis, and remediation.
PipeSmith implements the proven MAPE-K autonomic computing framework from academia—applied to data pipelines for the first time. This continuous feedback loop enables true self-healing.
Detect failures at execution layer in <100ms, not 5-30 minutes later.
LLM-powered diagnosis correlates logs, metrics, and schema changes in <500ms.
Select optimal remediation strategy based on historical success rates.
Apply fixes automatically in <1 second, no human required.
Every remediation improves future success rates through LLM fine-tuning.
Seamlessly integrate with your existing data stack—no rip-and-replace required.
Built with the reliability, security, and performance that enterprises demand.
Single execution model eliminates Lambda architecture complexity. Kappa-first approach.
Automatic PII detection, GDPR/CCPA compliance, audit trails for regulatory reporting.
10-100x faster than Python competitors. <1% pipeline overhead.
Your data becomes your competitive advantage. Success rate improves monthly.
Deploy across US, EU, APAC with timezone-aware scheduling and compliance.
Replace 5-10 separate tools with one platform. Observability + Orchestration + Healing.
Be among the first to experience autonomous self-healing pipelines. Join our waitlist for exclusive early access.
See how PipeSmith's 5-step process transforms a pipeline failure from a 1-hour incident into a 5-second automatic fix.
See the dramatic difference: 1 hour → 5 seconds
Traditional Stack
Self-Healing Platform
See how organizations transform pipeline failures from multi-hour incidents into seconds-long automatic fixes.
TechStartup (20 pipelines)
EnterpriseBank (347 pipelines)
DataCo (127 pipelines)
Real feedback from early adopters
"PipeSmith reduced our pipeline debugging from 4 hours to 15 minutes. Our engineers can finally focus on building features."
"We eliminated $5M in regulatory compliance risk with automatic governance. Game-changer for financial services."
Join our waitlist to experience autonomous self-healing pipelines and measurable ROI from day one.
We're building PipeSmith to eliminate pipeline firefighting once and for all. Observability isn't a bolt-on—it's the foundation. Self-healing isn't a dream—it's proven autonomic computing applied to data.
Not a bolt-on. Observability is core to the execution engine from day one.
Academic framework proven in autonomic computing, now applied to data pipelines.
Kappa architecture eliminates Lambda complexity. Single codebase, single mental model.
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Simple, predictable pricing based on pipeline count. Every tier includes autonomous self-healing, real-time detection, and measurable ROI.
Small teams (2-10 engineers, 1-20 pipelines)
Mid-market teams (10-50 engineers, 20-200 pipelines)
Large orgs (50-200 engineers, 200+ pipelines)
Customize your plan with additional features and capacity as needed.
Typical usage: 100-500 actions/month = $5-25K/month
Add pipelines beyond your plan limit
Dedicated support manager and 30-min SLA
Custom-built healing strategies for your specific failures
Join the waitlist now and save 40% for the first 6 months. Plus, get priority onboarding and direct access to our team.
Everything you need to know about PipeSmith's self-healing data pipelines.
PipeSmith instruments your pipeline execution at the source layer using Apache Arrow zero-copy data capture. We detect anomalies in real-time as pipelines run, not 5-30 minutes later via threshold-based monitoring. Our detection runs inline with your pipeline execution, catching schema drift, connection errors, and data quality issues the moment they occur.
90%+ of common failures: schema drift (column renamed/added), transient timeouts, source unavailability (reroute to replica), data quality issues (rollback), connection errors (retry with backoff), and more. Critical pipelines can require human approval before remediation. Our retry engine handles exponential backoff, fallback engine handles schema mapping, reroute engine switches sources, and rollback engine restores previous state.
No. PipeSmith works with your existing orchestration, transformation, and warehouse tools. We wrap your pipelines with observability and healing, not replace them. You keep your existing Airflow DAGs, dbt models, and Snowflake tables—we just make them self-healing. Think of us as an intelligent wrapper that detects, diagnoses, and fixes failures before they impact your business.
Every successful remediation becomes training data for our LLM. Over time, PipeSmith learns your organization's specific failure patterns. Month 1: 65% success → Month 12: 85%+. Your data stays private and is used only to improve your instance. We use RAG (Retrieval-Augmented Generation) to search for similar failures in your history, and LLM fine-tuning to specialize the model for your org.
Small companies save $77K/year (154% ROI). Mid-market saves $494K/year (330% ROI). Enterprise saves $7.2M/year (2,051% ROI). Primary savings: reduced firefighting time (62% of engineer time freed), eliminated SLA violations ($1M-$10M regulatory risk eliminated), tool consolidation (replace 5-10 separate tools), and compliance automation (automatic PII detection, GDPR/CCPA compliance).
Traditional tools alert you when something breaks—you still fix it manually (75 min average). PipeSmith detects AND fixes automatically (<15 seconds). We implement the MAPE-K autonomic loop: Monitor → Analyze → Plan → Execute → Knowledge. Observability tools stop at 'Monitor.' We go all the way to autonomous execution and continuous learning.
Our detection has <5% false positive rate with >90% true positive rate. For critical pipelines, you can require human approval before remediation (human-in-the-loop). We also include a confidence score (0-100%) with every diagnosis—you can set thresholds like 'only auto-remediate if confidence >80%.' And every action is logged to our audit trail, so you can always rollback.
Most customers are up and running in 2-4 weeks. We provide: (1) Guided onboarding with our team, (2) Pre-built connectors for common sources (Kafka, Snowflake, Postgres, S3, etc.), (3) Integration with your existing orchestration (Airflow, Prefect, Dagster), (4) Custom remediation strategies for your specific failures. No rip-and-replace—we wrap your existing pipelines.
Join our waitlist and our team will answer all your questions personally.
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154%-2,051% ROI with measurable savings from day one
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