How we evaluate cloud consulting partners
Independent assessment based on verifiable signals. No numeric score, no pay-to-rank.
The problem we're solving
Choosing a cloud consulting partner is a high-stakes decision with poor information. Most directories sell rankings. Review sites are gamed. Partner tier logos tell you about vendor relationships, not delivery quality.
Cloud Intel exists because IT leaders deserve honest, independent research — not a leaderboard that reflects ad spend.
Our approach
We act as an independent buyer's agent. We do not assign numeric scores. Instead, we assess each firm across five verifiable dimensions and document where that firm excels — and where it shouldn't be your first call. The goal is a clear fit assessment, not a ranking.
Firms can pay for one thing: a Verified tier that confirms their profile data is accurate and current (a single flat rate, clearly labeled). They cannot pay for editorial verdicts, change their documented strengths and considerations, influence the best-for / wrong-for assessments, or buy a higher position. Those are editorial, period.
How we source our data
Our research process is multi-source and focused on what's verifiable:
- Official partner registries: We verify partner tier and certifications directly from AWS Partner Network, Microsoft AI Cloud Partner Program, and Google Cloud Partner Advantage — not from firm self-reporting.
- Published case studies: We review the firm's own published work. Vague success stories get noted. Specific, metric-backed outcomes get weighted more heavily.
- Pricing research: We document engagement models and pricing transparency based on publicly available information and, where applicable, market benchmarks from published industry data.
- Specialization assessment: We compare stated focus areas against evidence of actual delivery — certifications, case study subjects, and team structure.
- Ongoing updates: Profiles are reviewed when firms achieve new certifications, publish new case studies, or when market conditions shift. We note when a profile was last updated.
The five dimensions we assess
Each dimension is evaluated on the evidence available. Where evidence is thin, we say so rather than fill the gap with assumptions.
1. Partner Tier & Certifications
We start with what's verifiable: official partner tier (AWS Premier, Azure Expert MSP, GCP Premier, etc.) and active competency certifications. These signal meaningful investment in the vendor relationship and establish a baseline for technical capability.
What we look at:
- • Cloud provider partner tier (Premier, Advanced, Select, Expert MSP)
- • Active competency and specialization badges
- • Individual staff certifications (AWS SA Pro, Azure Expert, GCP Pro)
- • Consistency of certifications relative to firm size
2. Documented Outcomes
Past performance is the best predictor of future performance. We look for evidence that a firm can deliver — not promises, but published results with enough specificity to evaluate.
What we look at:
- • Case studies with concrete metrics (cost reduction %, timelines, scale)
- • Verifiable client references
- • Awards, recognitions, or cloud provider spotlights
- • Industry-specific delivery experience
3. Pricing Transparency
Partners who won't discuss pricing until deep in a sales process often have rates misaligned with their clients' budgets. We treat transparency as a signal: firms confident in their value tend to be upfront about what engagements cost.
What we look at:
- • Willingness to share typical project ranges
- • Published rate cards or engagement model pricing
- • Clarity on fixed-fee vs. T&M vs. retainer structures
- • Absence of pure "contact us for pricing" stonewalling
4. Specialization Depth
Generalists exist, but specialists typically outperform them on specific workloads. A firm focused on AWS healthcare migrations will usually do better than one that handles everything for everyone. We assess whether stated specializations are real or just marketing.
What we look at:
- • Coherent focus area vs. laundry list of services
- • Industry vertical expertise with proof
- • Platform depth relative to multi-platform spread
- • Team size appropriate to stated project scope
5. Fit Signals: Best-For & Wrong-For
No firm is right for every buyer. We document the specific scenarios where a firm excels and — just as important — where it shouldn't be your first call. Explicit wrong-for assessments are more useful than vague cautions.
What we look at:
- • Client profile fit (startup vs. enterprise vs. mid-market)
- • Project type fit (net-new build vs. migration vs. managed services)
- • Budget range alignment
- • Red flags: thin track record, recent ownership change, mismatched team size
What you see on each profile
Each firm profile documents what we found across the five dimensions above. Instead of a composite score, you get:
- Partner tier and platforms: Official designation from the cloud provider's partner program.
- Strengths: What this firm demonstrably does well, based on evidence.
- Considerations: Honest gaps or caveats a buyer should factor in — thin documentation, narrow track record, pricing opacity.
- Best for: The buyer profile and project type where this firm is a strong fit.
- Wrong for: Scenarios where this firm is probably the wrong choice, even if they'd take the work.
- Pricing range: Documented engagement models where available.
The absence of a numeric grade is intentional. A single number can't tell a healthcare CTO whether a firm has handled HIPAA workloads — but a best-for assessment can.
Our business model
Cloud Intel is free for buyers. Firms can pay for a single Verified tier — a flat rate that confirms their profile data is accurate and current, clearly labeled. That is the only thing money can buy here.
You cannot buy:
- A ranking or a spot on a shortlist — list order is neutral, never pay-to-rank
- An editorial verdict — paid firms cannot change their strengths, considerations, or best-for / wrong-for assessments
- Anything hidden — the Verified label is the only paid signal, and it is always marked
Our value depends entirely on buyer trust. If our business model ever creates a conflict with honest research, we'll disclose it. We do not sell user data.