Beyond cloud.
Intelligent IT for enterprises & government.

Frontier AI crossed real thresholds — frontier models now beat expert humans on most graduate-level benchmarks. The leaders: OpenAI’s GPT-6 Astra (Sept 2026), Anthropic’s Claude, Google’s Gemini 3 with 1M-token context, xAI’s Grok — and open-weight rivals DeepSeek V4 and Qwen (942M+ downloads and counting) now within a few points of the frontier on everyday work. No single model is right; the winning setup is a routed mix — which is exactly what we deploy.

2026’s dominant shift: systems that plan and execute multi-step work, not chatbots. Agents jumped from ~12% to over 66% on real-computer benchmarks in a year — but still fail roughly one in three attempts. Meanwhile only ~9–18% of organisations orchestrate multiple agents, and 91% run agents while just ~10% manage their identities. The dependable pattern is an orchestrated, guarded, human-in-the-loop agent — how we ship them into production.

The Model Context Protocol — the open standard connecting AI models to your tools and data. It crossed 10,000+ servers and ~97M monthly downloads, is stewarded by the Linux Foundation’s Agentic AI Foundation, and shipped a stateless spec in July 2026 so it scales on ordinary load-balanced infrastructure. We use it to wire agents into your ERP, ITSM, VOIP and databases — no vendor lock-in.

Open weights now match closed models on most everyday workloads — the gap is ~3%, up from 0.5% in 2024 — while closed models still lead on the hardest reasoning. Self-hosting breaks even around ~8,000 conversations a day, and gateways that route simple jobs to small open models cut inference bills 20–40% (some firms report 73%). For regulated and government buyers, sovereignty usually closes the argument.

The EU AI Act’s high-risk obligations start applying from August 2026; ISO/IEC 42001 is the emerging management framework; NIST’s AI RMF is the practical risk guide. And as agents multiply, identity becomes the control plane — 91% of firms run AI agents but only ~10% have a strategy for non-human identities. We build auditability, model risk and agent-identity controls in from day one.

Real, and scaling fast. Local inference now runs trillion-parameter models (like DeepSeek V4) across a few machines via llama.cpp and quantized weights; NVIDIA-class AI factories are the government standard; Gartner predicts 65% of governments will mandate technology sovereignty by 2028. Our 24RACK gives you local LLMs, agents and RAG, air-gapped when required — your data stays yours.