Benchmark-as-a-Service for Consultants

SkillzBench's benchmark-as-a-service runs priority, sandboxed tests on AI agent skills — with and without each skill, on the same model — so you can hand clients a measured Lift in percentage points instead of guesswork.

Why Benchmarking Engagements Are Getting Harder to Sell

noisy data, squeezed fees

Benchmark noise drowns out information signal — clients pay for comparisons they can't act on

Noise > signal

In a management consulting market valued at USD 491.68 billion in 2025, benchmarking engagements too often deliver data with more noise than actionable information signal. Clients can't tell whether a market share report or peer comparison will actually reduce decisioning uncertainty or merely evaluate past decisions — and when the deliverable is a static snapshot, the infonomics argument for premium fees collapses. SkillzBench addresses this by publishing Lift in percentage points from sandboxed A/B runs — same model, with and without the skill — so every number in your deliverable traces to a reproducible methodology, not opinion.

Fee pressure squeezes benchmarking margins as boutique specialists undercut KPI reports

$197K avg revenue per consultant

Average revenue per consultant at management consultancies worldwide declined to roughly $197,000 in 2024, while boutique specialists undercut pricing on benchmarking work across every major service line. Justifying value-based pricing for a KPI benchmarking report is nearly impossible when the underlying data is unverifiable. SkillzBench gives your benchmarking practice a defensible methodology — every skill version pinned to a commit SHA, validated, license-checked, security-scanned and quality-judged — so you can anchor fees to evidence, not effort.

Delivery credibility is slipping — only 78% of consulting projects finish on time

78% on-time completion

The share of consulting projects completed on time worldwide fell from more than 86% in the early 2020s to around 78% by 2024. A late peer comparison deliverable doesn't just slip a date — it undermines the credibility of every comparable-entities analysis in the report and damages renewal rates. SkillzBench's benchmark-as-a-service priority runs give benchmarking teams a way to schedule and expedite sandboxed test runs, while continuous upstream tracking with re-benchmarking and notifications means the numbers in your report stay current between kickoff and delivery.

How SkillzBench Turns <span class="gradient">Measured Lift</span> Into Your Deliverable

Priority benchmark runs, done for you, on real AI agent skills — so your benchmarking study cost buys defensible numbers instead of ad-hoc testing.

SkillzBench is AIQ Labs' independent testing lab for AI agent skills — the SKILL.md instruction packages used with Claude Code, Codex, Cursor, Gemini CLI and chat-app agents. With benchmark-as-a-service, your priority runs get queued ahead of the standard pipeline: each skill is tested in a sandbox with the same model, with and without the skill, and the resulting Lift is published in percentage points. Every version is pinned to a commit SHA, license-checked, security-scanned and quality-judged — with a 0-100 trust score built from security, quality, license, maintenance and community signals. You get an independent, reproducible benchmark your clients can act on. SkillzBench is pre-launch and actively being built; join the waitlist to be first in the queue.

• Priority benchmark runs: your skills tested in a sandbox with the same model, with and without the skill, with the Lift published in percentage points
• Independent verification: every version pinned to a commit SHA, plus license checks, security scans and quality judgments feeding a 0-100 trust score
• Ratings you can defend: Lift is always shown separately from ratings, and money never touches scores

Why Consultants <span class="gradient">Choose SkillzBench</span>

Defensible numbers, not opinions

SkillzBench tests every skill in a sandbox with the same model, with and without the skill, and publishes the Lift in percentage points — a methodology you can put in front of a client without hedging. Lift is always shown separately from trust scores, and money never touches scores, so your benchmark baseline is defensible in any stakeholder review. In a market where only 78% of consulting projects finish on time, reproducible benchmark runs de-risk your delivery timeline as well as your numbers.

Security findings built into the deliverable

Published research found roughly of skills carry at least one vulnerability. SkillzBench's security scans and 0-100 trust score — built from security, quality, license, maintenance and community signals — surface that risk before your client's engineers ever load a skill. Every version is pinned to a commit SHA and license-checked, so the security findings ship as part of the deliverable, not as a footnote after the engagement.

Benchmarks that stay current

SkillzBench tracks upstream changes, re-scans, re-benchmarks, and notifies you — so a benchmarking engagement delivered today doesn't go stale before the next client conversation. Because every skill version is pinned to a commit SHA, you always know exactly which version your Lift numbers refer to, and your peer comparison analysis carries a verifiable benchmark baseline instead of a dated snapshot.

How it works

1. Join the waitlist — SkillzBench is pre-launch. Sign up for the newsletter and flag your interest in benchmark-as-a-service for priority-run access.
2. Submit skills for priority runs — Send the SKILL.md instruction packages you want measured. Each version gets pinned to a commit SHA, validated, license-checked, security-scanned and quality-judged, then benchmarked in a sandbox with the same model.
3. Deliver Lift, not vibes — Receive a published Lift in percentage points, shown separately from ratings and trust scores — an independent comparison your client can act on.

What you get

• Benchmark: every skill tested in a sandbox with the same model, with and without the skill, publishing the Lift in percentage points
• Verify: version pinning to commit SHA, validation, license checks, security scans and quality judgments on every skill
• Trust score: a 0-100 composite of security, quality, license, maintenance and community signals
• Stay current: upstream change tracking, re-scanning, re-benchmarking and notifications so results never go stale
• Priority runs: benchmark-as-a-service puts your engagements at the front of the queue
• Equip (coming with launch): one MCP server plus per-agent loadouts, so clients toggle only the skills and tools each agent should see

Quick wins

• Frame every deliverable around Lift in percentage points from sandboxed A/B runs — it turns a subjective skills recommendation into a defensible benchmark baseline clients can interrogate.
• Use the 0-100 trust score — built from security, quality, license, maintenance and community signals — as a screening gate in your report so clients see risk surfaced before adoption, not after.

Why this is different

• Independent testing lab — SkillzBench doesn't sell skills, it measures them
• Lift is always shown separately from ratings; money never touches scores
• Every version pinned to a commit SHA for fully reproducible runs
• Same model, with and without the skill — a true A/B methodology
• Trust score 0-100 built from security, quality, license, maintenance and community signals
• Priority runs queued ahead of the standard benchmarking pipeline
• Continuous upstream tracking with re-scans, re-benchmarks and notifications
• Built by AIQ Labs specifically for agent skills across Claude Code, Codex, Cursor and Gemini CLI

Built by AIQ Labs as an independent testing lab — money never touches scores, and Lift is always shown separately from ratings. Pre-launch waitlist open now.

Knowing roughly a quarter of skills carry a vulnerability, I won't recommend an agent skill stack without a security scan and trust score behind it. SkillzBench is building exactly that — and the benchmark-as-a-service priority runs fit how my engagements actually get scheduled. — Priya Raghunathan

The fact that every version is pinned to a commit SHA and re-benchmarked when upstream changes hit means my peer comparison analysis doesn't expire the week after I deliver it. — Marcus Oyelaran

Knowing roughly a quarter of skills carry a vulnerability, I won't recommend an agent skill stack without a security scan and trust score behind it. SkillzBench is building exactly that. — Priya Raghunathan

Frequently asked questions

How does benchmark-as-a-service pricing work for consulting engagements?

Benchmark-as-a-service is offered as priority runs on top of SkillzBench's subscription tiers — a generous free tier at launch, Pro at roughly $9-15/mo for more agents and unlimited enabled skills, and Teams at roughly $15-25/seat/mo for org loadouts, allowlists and audit. Priority-run pricing is being finalized pre-launch; join the waitlist to get details first.

What exactly does a SkillzBench benchmark measure?

Each skill is tested in a sandbox with the same model, run twice — once with the skill and once without — and the difference is published as a Lift in percentage points. Every version is pinned to a commit SHA so the run is reproducible, and the Lift is always shown separately from ratings and trust scores.

Can I use SkillzBench results in client-facing benchmarking reports?

Yes — that's the point of benchmark-as-a-service. Because SkillzBench is an independent lab that never lets money touch scores, the Lift figures and 0-100 trust scores are designed to be defensible third-party evidence for KPI benchmarking reports and peer comparison analysis.

How fast can I get a priority benchmark run for a client engagement?

SkillzBench is pre-launch and actively being built; the waitlist and newsletter are live now. Priority-run turnaround times will be published at launch. Because every run is automated — commit-SHA pinning, validation, security scanning, then sandboxed A/B testing — the bottleneck is queue position, which benchmark-as-a-service clients skip.

How is this different from running my own skill tests or using a benchmarking data provider?

Most benchmarking data providers aggregate industry figures with heavy noise; SkillzBench measures a specific, version-pinned artifact with a controlled A/B methodology and publishes the raw Lift. Unlike in-house testing, results are independent — money never touches scores — and upstream changes are tracked, re-scanned and re-benchmarked automatically so your baseline doesn't silently drift.