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Browse our services, roles, and resources at a glance.
AI / Web3 / emerging-tech companies need production LLM engineers, smart contract developers, and AI/ML specialists — exactly the talent pools that are most expensive and hardest to hire locally.
Emerging tech companies don't lose to better products. They lose to slower hiring.
AI / Web3 / emerging-tech companies need production LLM engineers, smart contract developers, and AI/ML specialists — exactly the talent pools that are most expensive and hardest to hire locally.
We'll map your specific ai · web3 · emerging tech ops gaps to the bench AB7 can deploy in 7–14 days.
Book the briefingWhat we hear from ai · web3 · emerging techoperators isn't a strategy gap — it's an execution gap. The roadmap is fine. The spreadsheet is fine. What's missing is the bench required to actually run it. That's what we built AB7 for.
Below: the five fires we keep finding inside this category. Each one maps cleanly to one of AB7's six service pillars — which is the point of the rest of this brief.
“Most ai · web3 · emerging techbuyers don't need more advice — they need staffed seats.”
Production LLM engineers in US/UK/AU markets quoted $200k-300k with rare availability. Series-A budgets break.
Solidity, Rust, Move developers in short supply globally. AB7 sources from blockchain-trained pools.
Foundation model training needs labeled data at scale. Specialized AI training data ops teams.
GPU-cluster ops, model deployment pipelines, vector database operations require AI-DevOps specialists.
AI Act (EU), Web3 securities laws — compliance specialists familiar with emerging-tech regulation.
One MSA covers all six. Add or drop pillars without re-papering the engagement.
Build the AI/Web3 engineering bench
Foundation model + agent training data at scale
Audit pre-deployment + AI safety ops
Build dev community + product-led growth
Token + crypto + multi-currency accounting
Source niche specialists at speed
A typical AI · Web3 · Emerging Tech engagement opens with 2–3 seats and expands. All seats sit under a single MSA.
Indicative monthly rates. Final pricing varies by seniority, geography (India / Philippines) and shape. Add headcount any time without re-papering the MSA.
Outcomes tracked weekly inside your shared dashboard — not promised in a deck.
The first 14 days are setup and absorption. Real movement on metrics begins around Day 30. By Day 90, the bench is steady-state and you're measuring outcomes — not the engagement.
Most ai · web3 · emerging tech operators recoup setup cost by Day 60 from a combination of savings + uplift on the metrics below.
Production LLM / RAG / agent systems shipped in 8-12 weeks
Smart contract development at 60-70% cost savings vs US/UK
AI training data ops scalable to 1000s of labels/week
Crypto + token accounting clean for compliance
Single MSA across all categories
No surprises at audit time. We sign your DPA, follow your stack, document everything in your dashboard.
We don't sell, resell, or distribute these platforms. Our remote staff operate on your existing accounts under your governance. All trademarks belong to their respective owners.
A composite drawn from real AI · Web3 · Emerging Tech deployments. Names redacted, structure intact.
Sydney Series-A AI startup needed senior AI engineer for production RAG + agents. AU market quoted A$200k+ with 8-week notice.
AB7 placed senior AI engineer with OpenAI + LangChain + Pinecone production experience in 14 days. Full AEDT overlap.
Production RAG shipped in 8 weeks. A$110k/yr saved. 12-month retention to date.
One MSA. Six pillars. A bench that already speaks ai · web3 · emerging tech. Your first hire goes live in 7–14 days.