Intelligence.Automated.Deployed.
Replace 6-person analyst teams with AI pipelines that process 3M+ data points daily and surface decisions in under 200ms.
Proven at Scale
Numbers that replace
the sales deck.
Every metric below is pulled from production deployments across 40+ engineering teams. No cherry-picked benchmarks — these are live SLA commitments.
Reduction in manual processing costs
Teams using DigiIntel replace repetitive analyst work within the first 30 days.
Data decisions per day
Our inference engine handles peak loads without degradation — guaranteed by SLA.
Platform uptime over 18 months
Zero-downtime deployments and multi-region failover built into every tier.
Average decision latency
From raw signal to structured output — faster than a human can blink.
Case Studies
Built by teams like yours.

Fintech cuts fraud detection latency from 4s to 180ms
Meridian Bank replaced their legacy rule-engine with a DigiIntel streaming pipeline. 2.1M transactions per day, sub-200ms decisions, zero false-negative misses in 6 months.
Meridian Bank
Financial Services

SaaS pipeline accuracy jumps from 61% to 94%
Predictive deal scoring for a $200M ARR SaaS company.
E-commerce ETL pipeline handles 10× Black Friday spike
Auto-scaling inference layer with zero manual intervention.

Healthcare SIEM reduces alert fatigue by 78% in 60 days
ClearPath Health deployed DigiIntel's anomaly classification layer on top of their existing SIEM. Alert volume dropped from 4,200/day to 920 high-confidence signals — with zero missed incidents in the first quarter.
ClearPath Health
Healthcare IT
Insights
Written by engineers,
for engineers.
Why your ML pipeline is 3× slower than it needs to be
Most teams over-engineer their feature stores and under-invest in inference serving. Here's what 40 production audits taught us.

The hidden cost of "human-in-the-loop" at scale
Streaming vs batch: the decision that defines your latency ceiling

Video · 24 min
DigiIntel Platform Walkthrough — May 2026
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