Why We Ran This Benchmark
Every enterprise AI vendor claims superiority. We decided to test ours — publicly, with methodology you can reproduce.
The benchmark was designed around one question: in regulated compliance workflows where accuracy failures have legal consequences, which system performs best across the full decision matrix of accuracy, latency, cost, and auditability?
We are not a neutral party. We built AsymiLink AI. We have done our best to design a fair benchmark, and we invite scrutiny of our methodology.
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Benchmark Design
Task Categories 1,200 total tasks
Category Count Description --------- HIPAA PHI Classification 300 Classify whether text contains PHI under 18 HIPAA identifiers SOC 2 Control Mapping 250 Map audit evidence to correct SOC 2 Type II control categories GDPR Lawful Basis Analysis 200 Identify applicable lawful basis for described processing activities Contract Risk Flagging 250 Identify high-risk clauses in commercial contract excerpts Financial Regulatory Screening 200 Screen transaction descriptions against AML/KYC rule sets
Ground Truth
All 1,200 tasks were reviewed and labeled by a panel of 3 subject-matter experts 2 compliance attorneys, 1 CISO with HIPAA/SOC2 background. Tasks where experts disagreed were excluded from scoring 118 tasks removed, final n=1,082.
Models Tested
- AsymiLink AI: Private fine-tuned ensemble on compliance corpora, deployed on-premises - GPT-5.5: OpenAI API, accessed May 2026, default temperature - Claude Opus 4.7: Anthropic API, accessed May 2026, default temperature
All models received identical prompts with no system-prompt tuning advantages for any model beyond what each vendor recommends for production use.
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Results
Accuracy
Task Category GPT-5.5 Claude Opus 4.7 AsymiLink AI ------------ HIPAA PHI Classification 91.2% 93.4% 97.1% SOC 2 Control Mapping 84.7% 87.2% 93.8% GDPR Lawful Basis Analysis 88.9% 91.0% 95.4% Contract Risk Flagging 86.3% 89.7% 94.2% Financial Regulatory Screening 83.1% 86.4% 92.7% Overall 86.8% 89.5% 94.6%
Latency p50 / p95
Model p50 Latency p95 Latency --------- GPT-5.5 1,840ms 4,200ms Claude Opus 4.7 2,100ms 5,800ms AsymiLink AI on-prem 380ms 920ms
Latency advantage is largely explained by on-premises deployment eliminating network round-trips to external APIs. Cloud-deployed AsymiLink AI narrows this gap to 40% faster than GPT-5.5.
Cost Per 1,000 Tasks
Model Input Tokens Output Tokens API Cost Infrastructure Cost Total ------------------ GPT-5.5 2.1M 420K $147.00 $0 $147.00 Claude Opus 4.7 2.1M 380K $168.00 $0 $168.00 AsymiLink AI N/A N/A $0 $31.40 $31.40
AsymiLink AI infrastructure cost calculated at AWS p4d.24xlarge spot pricing for the inference cluster used. Amortized over typical enterprise monthly volume 50K+ tasks/month, infrastructure cost per 1,000 tasks drops further.
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The Dimension That Changes Everything