Not proofs of concept. Not demos. Production-grade AI systems that survive contact with real data, real users, and real scale. We are the engineering behind the intelligence.
Trusted by teams at
We don't build demos. Every system we ship is designed for production workloads, real data, and continuous operation. Here's what we specialise in.
Purpose-built neural architectures designed around your data, your constraints, your infrastructure. We don't fine-tune and ship — we architect from first principles.
End-to-end pipelines from data ingestion through feature engineering, training, validation, and deployment. Fully automated retraining loops.
Forecasting engines that turn historical patterns into actionable predictions — demand, churn, anomaly detection.
Image classification, object detection, document understanding, conversational AI — deployed at the edge or in the cloud with production-grade reliability.
Technical due diligence, feasibility audits, architecture reviews. We help you decide what to build — and what not to.
We don't start writing code on day one. Every engagement begins with understanding your problem at a depth most teams skip.
We study your data landscape, identify gaps, define success metrics, and establish baselines. No model is selected until the problem is genuinely understood.
Rapid prototyping across multiple architectures. We benchmark, compare, and converge on what actually performs — not what looks good on paper.
Rigorous training with cross-validation, hyperparameter sweeps, and bias auditing. Every model earns its place through evidence, not assumption.
Production deployment with observability, drift detection, and automated retraining triggers. Models that stay sharp in the real world.
An intelligent pipeline that extracts structured data from resumes, scores candidates against job descriptions, and integrates with existing ATS workflows.
Classifies and routes incoming documents by type — invoices, contracts, forms — using a multi-modal CNN architecture with OCR augmentation.
Real-time defect detection on a manufacturing line — runs on edge devices, flags anomalies in under 200ms, feeds into a central dashboard.
“Aether didn't just deliver a model — they delivered a system that actually works at scale. The difference between their work and the typical AI vendor is night and day.”
