AI that starts with strategy, not software.
Reyem Tech delivers AI consulting for startups and SMBs across Canada and the US that need real results — not proof-of-concept theatre or an 18-month enterprise programme. We help you find the AI opportunities worth pursuing, evaluate vendors and models honestly, and ship production AI your team can actually own — using pre-built models and managed services, so your first working system lands in weeks, not quarters. No data science team required. No vendor lock-in. No hype.
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.
AI Readiness Assessment
Before recommending anything, we evaluate your data quality, processes, and team readiness.
You get: 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.
You get: Every use case scored against effort, data availability, and business impact.
Proof of Concept
A working prototype for your highest-priority use case in 2-4 weeks.
You get: Something concrete to show your board — and to validate assumptions before committing budget.
Production Implementation
From validated POC to production: integrated into your stack, monitored, maintainable by your team.
You get: A working AI system your team owns — not a prototype that dies when we leave.
Team Training
Hands-on training tailored to actual roles — not generic AI literacy slides.
You get: Role-specific training materials and workflows so adoption sticks.
Vendor & Tool Selection
We evaluate and shortlist the right models, APIs, and platforms for your needs — vendor-neutral.
You get: Vendor comparison matrix with pricing analysis and dependency risk flags.
Who This Is For: Startups and SMBs in Canada and the US Exploring AI
AI is not just for tech giants. We help startups and SMBs across Canada and the US adopt AI pragmatically — starting with a use case that matters.
The CEO Drowning in AI Hype
"Every board meeting and investor call tells me AI should be a priority. I can't tell which vendors are solving real problems versus selling solutions in search of a problem."
The Ops Leader Buried in Manual Work
"My team is copy-pasting data, manually triaging tickets, building reports in spreadsheets. I know automation exists but I can't afford a $200K failed project."
The Technical Founder Who Needs to Move Faster
"I have engineering skills but they're spent on the product. I need help evaluating AI opportunities without slowing down the roadmap."
The SMB Owner Preparing to Scale
"Competitors are talking about AI and I'm worried about being left behind. I need high-confidence, low-waste AI projects that justify cost in 90 days."
Common AI Adoption Concerns (And Honest Answers)
We hear these objections frequently from SMBs in Canada and the US exploring AI. Here is the honest answer to each.
"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 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.
AI Opportunity Assessment
2-3 weeks
Interview your team, audit data assets, map processes. You receive a written report with ranked opportunities and a recommended starting point.
Proof of Concept
2-4 weeks
Build a working prototype for your top priority. Something you can see, test, and share with stakeholders.
Production & Operationalize
4-12 weeks
Engineer to production standards, integrate with existing systems, document, train team, establish governance. A working AI system your team owns.
Decision gate:
After each phase, you decide whether to continue. No multi-year contracts, no lock-in.
Enterprise AI vs. Reyem Tech
Why the enterprise approach doesn't work for teams under 200.
| Reyem Tech | Enterprise AI Firm | |
|---|---|---|
| Timeline to first result | 4-6 weeks | 12-18 months |
| Total investment (first project) | $25K - $75K | $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 |
Results That Matter
Measurable outcomes from AI consulting engagements.
40%
Average reduction in manual processing time
90
Days from assessment to production AI system
3x
ROI within 12 months on AI investments
0
Vendor commissions biasing our recommendations
Who This Is NOT For
You need enterprise-scale AI with a dedicated data science team (we can refer you)
You want to buy an off-the-shelf AI tool and need installation support only
You're looking for a 12-month research project with no production deadline
You need AI for compliance-only purposes with no business outcome goal
How We Engage on AI Consulting
Applicable engagement depths — pick the one that matches where you are. Each is a real, scoped engagement, not a vague consultation.
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.
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.
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.
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.
Frequently Asked Questions
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 Readiness Assessment identifies the highest-impact opportunities specific to your business and data maturity.
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.
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.
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.
Yes. We evaluate OpenAI, Anthropic, AWS Bedrock, Azure AI, and open-source models with no reseller agreements or vendor commissions biasing our recommendations.
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.
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.
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.
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