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AI Consulting
Start with AI strategy. Build what earns its place.
Reyem Tech helps startups and SMBs across the US and Canada identify real AI opportunities, evaluate vendors, and implement production AI — without the enterprise price tag.
What We Deliver: AI Consulting That Ships, Not Slides
Practical AI adoption that solves real business problems — not hype-driven experiments that go nowhere. Our approach is outcome-first: every engagement ends with a decision you can defend or a working system you own.
Reyem Tech delivers AI consulting for startups and SMBs across the US and Canada seeking results, not proof-of-concept theatre or an 18-month enterprise programme. We identify worthwhile opportunities, evaluate vendors and models, and ship production AI your team owns. Pre-built models and managed services get a first system working in weeks, not quarters — without a data science team or vendor lock-in.
How Our AI Consulting Engagement Works
A structured approach that moves from discovery to measurable impact — in weeks, not quarters. Every phase has a decision gate so you never commit beyond what's working.
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2-3 weeks
AI Opportunity Assessment
Additional stakeholder conversations or deeper data review may be scoped separately; neither is guaranteed.
AI Readiness Assessment: Use information shared through intake and kickoff to assess data quality, processes, and team readiness; produce a prioritized opportunity list ranked by business impact, not technical novelty.
Use Case Identification: Structured workshops to surface automation and AI opportunities across your organization; prioritize them by effort, available data, and business impact.
Vendor & Tool Selection: Vendor comparison matrix with pricing analysis and dependency risk flags; shortlist the right models, APIs, and platforms for your needs, vendor-neutral.
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2-4 weeks
Proof of Concept
Validate the top use case with a working prototype.
Working Prototype: Build a working prototype in 2-4 weeks for your highest-priority use case, giving your board something concrete to review and helping validate assumptions before committing budget.
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4-12 weeks
Production & Operationalize
Integrate the validated system and establish governance.
Production Implementation: A working AI system your team owns: integrated into your stack, monitored, and maintainable by your team.
Team Training: Deliver hands-on training plus role-specific training materials and workflows for actual roles — not generic AI-literacy slides — to support adoption.
Phase 1 is available as a standalone fixed-fee program: the AI Adoption Roadmap — from $7,900, three weeks, no retainer required.
Decision gate:
After each phase, you decide whether to continue. No multi-year contracts, no lock-in.
THE DIFFERENCE
Enterprise AI vs. Reyem Tech
Why the enterprise approach doesn't work for teams under 200.
| Metric | Reyem Tech | Enterprise AI Firm |
|---|---|---|
| Timeline to first result | 4-6 weeks | 12-18 months |
| Total investment (first project) | $20K–$70K | $500K - $2M+ |
| Team required | Your existing team + us | Data scientists, ML engineers, DevOps |
| Production rate | 90 days to working system | 18+ months (many never ship) |
| Vendor lock-in | None — you own everything | Proprietary models, custom infrastructure |
WHO THIS IS FOR
Leaders we usually work with.
AI is not just for tech giants. We help startups and SMBs across the US and Canada adopt AI pragmatically, starting with a use case that matters.
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The CEO Drowning in AI Hype
Board meetings and investor calls make AI a priority; separate vendors solving real problems from those pitching a solution without a use case.
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The Ops Leader Buried in Manual Work
Automate copy-pasted data, manual ticket triage, and spreadsheet reports without risking a $200K failed project.
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The Technical Founder Who Needs to Move Faster
Keep engineering focused on the product while evaluating AI opportunities that will not slow the roadmap.
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The SMB Owner Preparing to Scale
Choose high-confidence, low-waste AI projects that justify their cost within 90 days as competitors adopt AI.
The Reyem Tech ladder
Four buyable rungs. Pick the one that matches where you are. Each step is a real, productized engagement — not a vague consultation.
Technology Health Check
For AI, the Health Check answers the question that comes first: is your data and tooling actually in shape to do anything useful, and where would AI realistically pay off? It's the standard $2,000 fixed-scope review of your stack, architecture, team, and risk — automation-assisted, with a written report and a 60-minute readout in about two weeks. The deeper opportunity mapping, proof of concept, and production build live in the advisory and hands-on tiers.
Advisory
Ongoing AI strategy advisory: vendor and model evaluation (OpenAI, Anthropic, Bedrock, open-source), use-case prioritisation, and governance guidance on a monthly retainer — you keep the keys, we keep the roadmap honest and the spend justified.
Hands-on management
We embed to build the proof of concept and operationalise it: a working AI system integrated into your stack, monitored, documented, and handed to your team — not a prototype that dies when we leave.
Execution-Ready
Before you ask.
We hear these objections frequently from SMBs in the US and Canada exploring AI. Here is the honest answer to each.
Frequently Asked Questions
"Our data is a mess. We're not ready."
Most companies say this. Rarely is it a blocker. Our assessment tells you exactly what data quality each use case requires — and identifies opportunities that work with data you already have.
"We tried an AI tool and it didn't stick."
Tools without workflow integration and team buy-in fail every time. We design adoption into the implementation — not as an afterthought.
"AI sounds expensive to get wrong."
That's why we build the POC before asking for a large commitment. Contained experiment, proven value, then scale.
"We're too small for enterprise AI."
Our work is purpose-built for teams of 5 to 200. Pre-built models, APIs, managed services — Fortune 500 capability at SME-appropriate cost.
How do I know if my business is ready for AI?
If you have repetitive processes, large amounts of data, or customer-facing workflows that could benefit from automation or personalisation, you are likely ready. Our AI Adoption Roadmap identifies the highest-impact opportunities specific to your business and data maturity.
Do we need a data science team to adopt AI?
No. Most impactful AI today is built on pre-built models, APIs, and managed services — no dedicated data science team required. We choose the approach that fits your resources and goals.
What is the difference between AI consulting and just buying AI tools?
Buying tools without strategy leads to shelfware. AI consulting ties every investment to a business outcome, integrates it into your workflows, and drives adoption by your team. Strategy first, tools second.
How much does AI consulting cost in the US and Canada?
Pricing follows our engagement ladder, scoped to what you need. The entry point is the $2,000 Technology Health Check (~2 weeks, written report). Ongoing AI advisory is from $2,750/month; hands-on is from $8,000/month (an embedded fractional CTO), and a typical proof-of-concept-through-production build — fractional CTO plus developers at $50–$100/hour — runs around $20K–$70K (far below enterprise AI firms quoting $500K–$2M for multi-year programs). These are typical averages for planning only — actual cost is assessed per project and scope, and is not a guaranteed price. We share specifics on the first call.
Are you vendor-neutral?
Yes. We evaluate OpenAI, Anthropic, AWS Bedrock, Azure AI, and open-source models with no reseller agreements or vendor commissions biasing our recommendations.
Will AI replace our team?
No. We focus on removing repetitive work so your team can spend time on higher-value activities. AI augments capacity — it does not replace people.
How do you handle data privacy and responsible AI?
Responsible AI is built into every engagement: data-handling policies, human-in-the-loop checkpoints, audit trails, and compliance documentation appropriate to your industry and to Canadian privacy law.
Can SR&ED tax credits apply to AI projects?
Often, yes. SR&ED credits can apply to AI work involving genuine technological uncertainty and systematic experimentation — custom model training, novel integrations, or experimental architectures. We document the engagement to support a claim and recommend pairing with a specialised SR&ED accountant.
$2,000 · ~2 weeks · credited on month 3
Not sure where to start?
Vendor-neutral · priced before we start. A Technology Health Check is a fixed-scope engagement. Two weeks, written report, clear next steps — no open-ended commitment.