NirnAI OS centralizes your scattered data to deploy analytics, workflows and ML models.
See NirnAI OS turn your scattered data into running systems. Live, in 30 minutes.
Email classifier
Run #2418 · 09:41:22 · 1,204 messages
Auto-routed
96.4%
Avg. latency
412 ms
Escalated
38
Platform
Every source — warehouses, SaaS tools, spreadsheets, sensors — is centralized into a living ontology: one shared model of your business that stays current as your data moves. Everything you build afterwards speaks that same language.
120+
native connectors
~4 hrs
idea to app
0
engineers required
Sources
Outputs
Use cases
Distributor sell-out, panel data and pricing merged daily per SKU and banner.
What you get
Describe the outcome in plain language. NirnAI OS drafts the pipeline, the model and the interface, then shows you the run before anything goes live.
Native, incremental, monitored.
Escape hatch whenever you need it.
@nirnai.step("score_invoices")
def run(ctx):
df = ctx.table("Invoice")
return model.predict(df)09:41:02 INFO ingest.postgres — 12,480 rows synced
09:41:07 INFO ontology.map — entity `Invoice` reconciled (3 sources)
09:41:11 WARN workflow.dunning — retry 1/3 on payer API timeout
09:41:14 INFO workflow.dunning — recovered, 218 invoices queued
09:41:20 INFO model.classifier — batch scored, p95 412ms
MRR
$1.27M
Churn
2.1%
Active
8,431
How it works
01
Plug in databases, SaaS tools, APIs, files and sensors. Sync starts in minutes.
02
Map your sources into one ontology so every team shares the same definitions.
03
Describe the outcome you want. NirnAI OS assembles the workflow, model and UI.
04
Ship it, watch every run, and iterate without waiting on an engineering queue.
Bring one messy process. We'll have it running on NirnAI OS before your next board meeting.