Hire AI Consultants Whose Advice Comes With Code
Most AI consulting ends at a slide deck. Hire AI consultants through Aizecs and the arrangement is different by design: the senior engineer-consultants who audit your workflows and write the roadmap are the same people — or the same team — who then build it in your repos. Named consultant profiles arrive within 48 hours of your intro call.
48h
Consultant profiles in hand
2–3 wks
Typical AI audit sprint
$45/hr
Senior consulting from
4+ hrs
Daily overlap, US Eastern
Transparent Pricing
Consulting Rates That Don't Require a Procurement Cycle
Big-4 AI advisory starts around $300/hr and climbs, with implementation billed separately by a different team. Our consultant-engineers charge specialist engineering rates — and they stay to build.
| Role / Seniority | Aizecs (India) | Toptal / Turing | Upwork Freelancers | US In-House |
|---|---|---|---|---|
| Mid-Level AI Consultant (3–5 yrs) | $28–$50/hr | $90–$130/hr | $40–$70/hr | $150–$190/hr |
| Senior AI Consultant (5–8 yrs) | $45–$80/hr | $110–$160/hr | $50–$90/hr | $180–$230/hr |
| Principal AI Consultant / Lead (8+ yrs) | $55–$85/hr | $130–$180+/hr | $60–$100/hr | $200–$250/hr |
| Generative AI Engineer (build phase) | $45–$80/hr | $110–$160/hr | $50–$90/hr | $180–$230/hr |
Hourly rates for dedicated engagements, 2025–26 benchmarks. Marketplace and Upwork columns show comparable AI-specialist rates; big-4 strategy advisory typically bills $300–$600+/hr with implementation contracted separately. US in-house reflects a fully loaded AI lead hire.
How It Works
Audit, Roadmap, Build — One Continuous Thread
The engagement is structured so knowledge never gets lost in a handoff: the people who diagnose are the people who deliver.
Frame the opportunity
A 30-minute call on your business, workflows, and what you suspect AI could do. We'll flag immediately if your idea is a two-week API build rather than a consulting engagement.
Meet consultants within 48 hours
Named profiles of consultant-engineers with relevant industry and production-AI experience. Interview them on judgment: where AI fails, what they'd cut from your idea, how they measure ROI.
Run an audit sprint
Two to three weeks mapping your workflows against what current AI can reliably do — ending in a prioritized roadmap with effort estimates, cost models, and a build-vs-buy call for each opportunity.
Build with the same team
When you greenlight items, the consultant leads implementation — solo or with Aizecs engineers — inside your repos, month-to-month, with 30 days' notice to pause or stop.
Roles We Staff
Consulting Capabilities on the Bench
AI consulting spans strategy and deep implementation. These are the six capability areas our consultant-engineers cover most.
AI Opportunity Auditors
Systematically map your workflows to AI leverage points, score them by ROI and feasibility, and kill the ideas that sound impressive but won't survive contact with your data.
LLM Product Strategists
Define what an AI feature should actually do — scope, guardrails, model choice between Claude/GPT APIs and self-hosted options, and the eval criteria for 'good enough to ship'.
AI Architecture Consultants
Design the technical foundation: RAG over your knowledge base, vector databases like pgvector or Pinecone, agentic workflows, and integration with your existing systems.
Process Automation Consultants
Find the back-office work LLMs genuinely automate — document processing, triage, reporting — and design human-in-the-loop controls where errors are expensive.
AI Readiness & Data Consultants
Assess whether your data, infrastructure, and team can support what you want to build, and produce the concrete remediation plan when they can't yet.
Implementation Leads
The build-phase role: a consultant who carries the roadmap into sprint plans and leads Aizecs or in-house engineers to shipped, measured outcomes.
Why Aizecs
Consulting Without the Consulting-Industry Problems
The classic failure modes — junior staff behind a senior pitch, recommendations nobody can build, invoices before outcomes — are structurally designed out of how we work.
Builders giving the advice
Every consultant has shipped production AI systems. Recommendations come pre-filtered by 'could I build this?' — because they'll be asked to.
No pitch-team switcheroo
The named consultant you interview does the work. There's no partner selling and analyst delivering — a big-4 pattern we deliberately don't replicate.
Trial week applies here too
Consulting engagements start with a paid trial week like everything we do. Unconvinced after week one? That's the entire cost, replacement free.
Deliverables you can execute
Roadmaps arrive with architecture sketches, effort estimates, and cost models — specific enough that any competent team could build from them, not just ours.
Same-day working hours
4+ hours of daily overlap with US Eastern and near-full EU/UK coverage mean workshops and stakeholder sessions fit inside your calendar.
Findings stay yours
Audit outputs, roadmaps, and all built software are covered by IP assignment and NDA under a US-enforceable MSA. We don't recycle your strategy elsewhere.
Engagement Models
Three Consulting Engagements, Sized to the Decision
Start as light or as committed as the situation warrants — each model flows naturally into the next if you choose to continue.
AI audit sprint
A fixed 2–3 week engagement: workflow mapping, feasibility scoring, and a prioritized AI roadmap with cost and effort estimates for each opportunity.
Best for: Leadership teams deciding where AI fits first
Embedded AI consultant
A senior consultant-engineer joins your team part- or full-time as ongoing AI counsel — evaluating vendors, shaping features, and prototyping alongside your staff.
Best for: Companies wanting continuous AI judgment in-house
Consultant-led build team
The consultant who wrote your roadmap leads 2–4 Aizecs engineers through implementation, owning delivery from first sprint to measured production outcomes.
Best for: Executing the roadmap without an internal AI team
Compare Your Options
Aizecs vs the Usual AI Consulting Options
How consultant-engineers compare with strategy firms, freelance advisors, and hiring an AI lead yourself.
| Aizecs | Big-4 / Strategy Firm | Freelance Consultant | In-House AI Lead | |
|---|---|---|---|---|
| Senior consultant rate | $45–$80/hr | $300–$600+/hr | $50–$150/hr | $200–$250/hr loaded |
| Who does the work | The consultant you interviewed | Junior staff, partner oversight | The individual, capacity-limited | Your hire, once found |
| Builds what it recommends | Yes, same team ships it | Rarely — separate SOW | Sometimes, solo pace | Yes, but needs a team |
| Time to start | ~1–2 weeks | 4–8 weeks + procurement | Days to weeks | 3–6 months to hire |
| Risk containment | Paid trial week, free swap | Large minimum engagement | Reference checks only | Full mis-hire exposure |
FAQ
Common Questions
Why hire AI consultants from Aizecs instead of a big consulting firm?
Three structural differences: our consultants are practicing engineers who build what they recommend, the person you interview is the person who does the work, and senior rates run $45–$80/hr against $300–$600+/hr at strategy firms. The output is a roadmap plus working software — not a deck plus a second SOW.
What happens in an AI audit sprint?
Over 2–3 weeks the consultant interviews your team, maps workflows, and tests feasibility against your actual data and systems. You get a prioritized roadmap: each opportunity scored for ROI and risk, with architecture direction, build-vs-API recommendations, and effort estimates. It's designed to be executable by any team, including yours.
How much does it cost to hire AI consultants through you?
Mid-level consultants run $28–$50/hr, senior $45–$80/hr, and principal-level $55–$85/hr. A typical 2–3 week audit sprint with a senior consultant lands roughly in the $4,000–$10,000 range depending on scope — a fraction of a strategy-firm discovery phase, and it starts with a paid trial week.
Are your consultants actually hands-on with current AI tooling?
Yes — it's the admission requirement. Every consultant has shipped production systems on Claude or GPT APIs, built RAG pipelines with vector databases, and worked with agentic frameworks and eval tooling. Fewer than 1 in 20 applicants pass that bar, and pure-strategy backgrounds without shipping experience don't qualify.
Can the same consultant lead the implementation afterward?
That's the intended path. After the audit, the consultant can embed with your team or lead a build team of 2–4 Aizecs engineers through implementation, month-to-month with 30 days' notice. No knowledge handoff, no re-discovery phase, no second procurement cycle.
We're not sure AI applies to our business — is a consultation still useful?
That uncertainty is exactly what the audit sprint resolves. Sometimes the honest answer is 'not yet' — data isn't ready, or the ROI isn't there — and we'll deliver that conclusion with a remediation plan rather than manufacture a project. The intro call itself often settles whether an audit is even warranted.
How is confidentiality handled during an audit of our internal workflows?
Everything operates under a US-enforceable MSA with NDA and full IP assignment before any discovery begins. Consultants work inside your systems under your access controls, and all findings, roadmaps, and code belong exclusively to you. We never reuse client-specific strategy across engagements.
Get an AI Roadmap That Someone Will Actually Build
One 30-minute call to frame the opportunity, named consultant profiles within 48 hours, and an audit sprint that ends in decisions — not decks.
If the roadmap earns a greenlight, the same team builds it in your repos, month-to-month, starting with a paid trial week.
No commitment, no discovery-phase invoice. If AI isn't the right investment for you yet, that's the advice you'll get.