Defining how your business works shouldn't require architects and infrastructure planning.
Enter continuous inference – your rules evaluate against live data. When patterns match, new data flows.
Every outcome traced. Ship in minutes, not sprints.
Defining how your business works shouldn't require architects and infrastructure planning.
Enter continuous inference – your rules evaluate against live data. When patterns match, new data flows.
Every outcome traced. Ship in minutes, not sprints.
Avoid translating business requirements to infrastructure language and code.
Rules activate when conditions match, according to predefined patterns, priorities and service level objectives.
Data-to-Outcome
Observable
Traditional databases are full of insights but have little agency. Inferal transforms black boxes of code into observability-by-design pipelines.
Run workloads as close to the data as possible with edge computing and hybrid inferencing.
A highly optimized library that can be integrated into host applications for lowest latency.
Define inference patterns like SQL queries, but they run continuously and trigger actions when conditions are met.
Write declarative patterns that describe relationships between data. Like SQL, but activated when matched instead of when asked.
Real-time Sync
Switching Costs
Integrate with Postgres via Change Data Capture, messaging queues, APIs, and other data sources. All relevant data is considered in real-time.
Instead of building brittle triggers and notification queues, actionable data is acted upon as soon as possible with the least overhead.
Inferal Architecture@inferal
Every pattern is recorded, as is every successful match. Monitor, reflect, adapt, and heal your system in real-time with complete operational analysis.
Integrate with databases, LLMs, and development tools. Keep your current infrastructure intact and grow organically.
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Traditional agents spend most of their time asking questions: polling stock prices, checking inventory levels, querying patient records, monitoring sensor data.
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Infrastructure tools like Kubernetes and Terraform let you describe what you want – replica counts, network configs, resource limits – instead of strict guidelines.
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Financial systems generate thousands of transactions per second, each potentially triggering compliance checks, fraud detection, or risk calculations.
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Carrier rules, partner constraints, and compliance policies shift constantly. Exceptions multiply. Every decision needs explaining.
Learn moreHear from engineers who are building the next generation of reactive data systems with Inferal.
We replaced 2,000 lines of polling code with a handful of inference patterns. Our fraud detection now triggers in milliseconds instead of minutes.
Sarah Chen
Staff Engineer, Fintech Startup
The CDC integration was seamless. We kept our Postgres setup and just started getting real-time inferences. No migration, no downtime.
Marcus Rodriguez
CTO, Series B SaaS
Finally, a system that understands data flows instead of just storing data. Our ETL pipelines are now reactive instead of scheduled.
Emily Nakamura
Lead Data Engineer
Inference patterns feel like SQL queries that never stop running. Once you get it, you can't go back to traditional event handlers.
James Okonkwo
Principal Architect
Our LLM agents needed real-time context. Inferal bridges the gap between our vector store and live database state beautifully.
Anna Petrov
AI Platform Lead
The observability is incredible. We can trace exactly why an inference fired and debug production issues in seconds, not hours.
David Kim
SRE Manager
"We ran Inferal in shadow mode for two weeks before switching over. Validated every inference against our legacy system. Zero surprises on launch day."
Lisa Wong
VP Engineering, HealthTech
"The logical replication integration is chef's kiss. We're streaming 50k events/sec and Inferal keeps up without breaking a sweat. Our DBA actually smiled."
Alex Morris
Backend Lead, E-commerce
"When something goes wrong, I can see the exact data state that triggered each inference. It's like having a time machine for your business logic."
Priya Sharma
Platform Engineer, Logistics
We're seeking design partners to engage in pilot projects. You don't owe us anything unless we succeed.
