Enterprise AI runs 18 months. We don't do that.
We build focused, measurable AI systems for teams of 5 to 200, using pre-built models and managed services — so your first working AI solution ships in weeks, not quarters. No data science team required. No vendor lock-in. No hype.
What We Deliver
Practical AI adoption that solves real business problems — not hype-driven experiments that go nowhere.
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.
Responsible AI Governance
Governance from day one: data handling policies, human-in-the-loop checkpoints, audit trails.
You get: Compliance documentation, governance framework, and monitoring setup.
Vendor & Tool Selection
We evaluate and shortlist the right models, APIs, and platforms for your needs.
You get: Vendor comparison matrix with pricing analysis and dependency risk flags.
Who This Is For
AI is not just for tech giants. We help businesses of all sizes adopt AI pragmatically.
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."
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
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
Common Concerns
We hear these objections frequently. 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 AI tools at SME-appropriate costs.
How It Works
A structured approach that moves from discovery to measurable impact.
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 strategy 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
Frequently Asked Questions
If you have repetitive processes, large amounts of data, or customer-facing workflows that could benefit from personalization or automation, you are likely ready. Our assessment identifies the highest-impact opportunities specific to your business and data maturity.
No. Many impactful AI solutions can be implemented using pre-built models, APIs, and managed services without a dedicated data science team. We help you choose the right approach for your resources and goals.
Buying tools without strategy leads to shelfware and wasted budgets. An AI strategy ensures every investment is tied to a business outcome, integrated into your workflows, and adopted by your team. Strategy first, tools second.
Responsible AI practices are built into every engagement. We help you evaluate data privacy implications, implement appropriate safeguards, ensure transparency in AI-driven decisions, and comply with relevant regulations.
ROI depends on the use case. Common outcomes include 30-50% reduction in manual processing time, improved customer response rates, better demand forecasting, and new revenue streams from data-driven products. We help you define measurable KPIs before implementation.
Assessment: 2-3 weeks. Proof of Concept: 2-4 weeks. Production: 4-12 weeks. Most clients see a working system within 90 days.
No. We focus on eliminating repetitive work so your team can focus on higher-value activities. AI augments your team's capacity — it doesn't replace them.
Yes. We evaluate OpenAI, Anthropic, AWS Bedrock, Azure AI, and open-source models. No reseller agreements or vendor commissions biasing our recommendations.
We share pricing on the first call — no discovery engagements designed to sell the next phase. Typical AI assessment: fixed-fee engagement. POC and production work scoped and priced per project.
