30,358 senior-architect notes. Every answer cited. Zero invented flags.
Three years of NVIDIA DGX, RKE2 + OpenShift, Run:AI, Slurm, and NCCL-at-scale work — pre-solved and indexed. Ask anything between BIOS and a running training job. If the corpus can't ground an answer, the agent refuses to invent one and routes you to the human directly.
Three years of senior-architect work across
How it works
Three steps. No procurement cycle. No NDA. No two-week SOW negotiation.
Tell us what you're stuck on
Two-sentence form. We don't try to qualify you to death — if it's AI infra, we can help.
30-minute live call
Voice + face on a real WebRTC call. You can show your terminal or dashboard via camera. The agent has a 30,000-chunk memory of senior-architect notes.
Walk away with a fix
Citations under every claim. Transcript emailed after the call. If we couldn't help, you don't pay — money back guarantee.
Why this isn't ChatGPT
Generic LLMs read public docs and invent the rest with confidence. We read private senior-architect notes and refuse to answer when we can't cite a source.
Every claim cited, not hallucinated
30,358 chunks indexed from three years of senior-architect engagement notes. Every technical claim — flag name, version, command, file path — must trace to a specific source excerpt. Click any citation under an answer and see exactly which note it came from.
Truth gate — refuses to invent
Confidence floor 0.42 on retrieval. Below it, the agent says "I don't have specific notes on that" and routes you to AmiHai. Generic LLMs maximize satisfaction; we optimize for truth. That's the entire reason a senior engineer would trust this over ChatGPT.
Senior-architect depth, not generic DevOps
"Why does my NCCL all-reduce hang at 47%?" "My Run:AI scheduler ignored a quota after the 2.16 upgrade." "What's the canonical registries.yaml for an air-gap RKE2 cluster?" "Slurm prolog evicts pods OpenShift-side — what gives?" The unsexy half of the AI stack — between BIOS and a running training job.
Direct line to AmiHai when corpus is silent
If grounding fails, the agent doesn't lie — it routes the question to AmiHai. Email reply within 24h. The human you're paying for actually exists and reads your question. Not a chatbot saying "please consult our help center."
Voice + camera, not text chat
Real WebRTC call with a face. Show the broken nccl-test output via your camera; the agent reads it and responds. 1-2 second turn-around, native barge-in. Text chat is fine for static questions; live calls are how engineers actually solve hard problems.
EU residency + redacted PII
Everything runs in europe-west3 (Frankfurt). Identifying patterns — emails, IPs, API keys — are scrubbed from the corpus before reaching the LLM and the chat panel. Eligible for Israeli enterprise data rules.
What senior AI-infrastructure consulting actually costs.
Published rates for the work Altostratus does. The hour you spend sourcing the right consultant is itself an hour you're billed for.
1 Published engagement letters & retainer disclosures (MBB).
2 Big-4 advisory rate cards + Glassdoor consultant compensation reports.
3 AI Infrastructure Engineer Survey 2026 — median & 75th-percentile blended rates.
4 Vendor Pro-Services rate cards (NVIDIA, Dell Technologies, Lambda).
Common questions
Is this an actual person?▾
No. Altostratus is an AI consultant trained on AmiHai Habani's three years of senior-architect notes (NVIDIA DGX, RKE2, Run:AI, HPC, air-gap, network fabrics). AmiHai is the human; the agent speaks his expertise on his behalf. If a question is outside the corpus, the agent escalates to AmiHai directly.
What does "grounded" mean here?▾
Every non-trivial technical claim — a flag name, version, config snippet — must be backed by a chunk in the private corpus. If no chunk passes the confidence threshold, the answer is replaced with "I don't have specific notes on that" and routed to AmiHai. No invented kubectl flags.
Why a face / voice?▾
Because debugging cluster failures is conversational. Show me the broken nccl-test output via your camera, ask follow-ups, get a fast turn-around. Text chat is fine for static questions; live calls are how engineers actually solve hard problems.
Where is data stored?▾
Transcripts are stored encrypted in europe-west3 (GCP Cloud SQL). Identifying patterns (emails, IPs, API keys) are redacted before reaching the LLM and the UI. No transcript leaves the EU region.
Can I use this for an Israeli enterprise with strict data rules?▾
Yes — that's exactly the use case. Voice + RAG runs entirely in europe-west3. Custom on-prem / air-gap deployment is available on the Team / Enterprise tier.