Production systems, shipped with an SLA attached.
Every engagement scopes to your infrastructure, deploys to your environment, and runs under a signed SLA. We own the outcome, not just the model.
What we build and own for you
Natural Language Processing
Computer Vision
Predictive Analytics
Document classification, entity extraction, and semantic search pipelines—deployed to your stack with P99 latency targets in the SLA.
Object detection, defect identification, and real-time video inference running in your data center or cloud VPC with guaranteed throughput.
Demand forecasting, churn prediction, and risk scoring models embedded directly into your data warehouse with monitored drift detection.
Recommendation Systems
AI-Driven Automation
Model Development and Deployment
Collaborative and content-based engines built for your catalog scale, with A/B testing infrastructure and revenue-lift measurement baked in.
Workflow automation and intelligent routing systems that replace manual queues—delivered with rollback procedures and production runbooks.
End-to-end model lifecycle: training, versioning, CI/CD pipelines, and canary rollouts into your existing Kubernetes or cloud-native environment.
Data Pipeline Optimization
AI Consulting and Roadmapping
Batch and streaming pipelines architected for reliability—Kafka, Spark, dbt, or your preferred stack—with SLA-governed ingestion and alerting.
Technical scoping, build-versus-buy analysis, and infrastructure readiness audits—every engagement ends with a deployment plan, not a slide deck.
Four steps from scope to monitored production
99.9% uptime — guaranteed, contractual.
P99 API latency targets — published per service.
We scope your infrastructure, agree on measurable outcomes, build under a signed SLA, and hand over a live system with a dedicated on-call contact.
Incident response — under 15 minutes, 24/7.
NDA on first contact — no exceptions.
Step 1 — Infrastructure audit and gap analysis.
Step 2 — Scoped proposal with SLA terms and delivery milestones.
These are contract terms, not marketing targets. If we cannot commit to the metric, we decline the engagement.
Step 3 — Build, test, and staged rollout inside your environment.
Step 4 — Handover with runbooks, dashboards, and active monitoring.
Ready to scope your first deployment?
Bring your infrastructure constraints. We will scope the engagement, commit to an SLA, and start building—no introductory PDF required.
AETRIS-AI Labs
Shipped. Monitored. Guaranteed.
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(C) 2026 AETRIS-AI Labs | Production AI infrastructure for teams who cannot afford downtime.
Shipped. Monitored. SLA-backed.
