Federated Training Infrastructure
How we coordinate gradient updates across geographically distributed compute clusters while maintaining data sovereignty and training stability at global scale.
AICONSORTIUM · Resources · Engineering
Engineering at AIC
Technical Deep-Dives into the systems, architectures, and decisions that power the sovereign AI frontier.
Infrastructure
Research
Open Engineering
Engineering
How we actually build it
Deep-dives into the systems behind Clark: training, expert routing, and the federated mesh that runs inference across sovereign nodes.
Read the tutorials
Core Topics
Engineering Deep-Dives
Sparse MoE Routing Implementation
The engineering details behind our sparse Mixture-of-Experts router, covering token dispatch algorithms, load balancing, expert capacity buffers, and avoiding routing collapse during training.
Multilingual Tokenisation at Scale
Building a tokeniser that honours the morphological richness of 100+ world languages, across Latin, Devanagari, Perso-Arabic, Brahmic, and CJK scripts, while maintaining competitive token fertility ratios.
Low-Latency Inference Serving
Techniques for achieving sub-200ms first-token latency in production: continuous batching, PagedAttention, speculative decoding, and our custom KV cache management layer.
Evaluation Framework Design
Our internal eval harness for multilingual benchmarks, safety red-teaming, factual grounding tests, and alignment measurement, built to surface regressions before they reach production.
Data Pipeline for Sovereign Training
End-to-end data engineering: sourcing, deduplication, quality filtering, PII redaction, and domain-stratified mixing, all within controlled, sovereign jurisdictional boundaries.
Latest Posts
From the Engineering Blog
12 March 2026
How We Reduced Routing Collapse by 87% in Late-Stage MoE Training
A detailed post-mortem on expert load imbalance we observed at 40B tokens and the auxiliary loss modifications we used to fix it.
Engineering Team
28 January 2026
Building a Multilingual Tokeniser: Lessons from 100+ Languages and Multiple Script Families
We walked through our token fertility analysis across Devanagari, Perso-Arabic, Tamil, and Bengali scripts and the tradeoffs we made in vocabulary size.
Language Infrastructure Team
5 November 2025
Achieving Sub-200ms First-Token Latency Without Sacrificing Quality
Our inference serving architecture, built on speculative decoding with a draft model, flash attention v3, and a custom KV eviction policy, and the benchmarks behind it.
Inference Systems Team
Join Us
Build the Future of Sovereign AI
We are looking for engineers who want to work on hard, important problems at the frontier of AI infrastructure.