Enterprise AI Evaluation & Optimization

Stop Overpaying for LLM Quality.

Most enterprises waste $15,000–$20,000 monthly running the wrong models on the wrong tasks. BlanEval finds exactly where quality drops and costs spike , then fixes both.

Interactive Lab

See the Difference Yourself

Pick any two models from 15 options. Switch across 6 enterprise use cases. See exactly where quality and cost diverge.

AModel A
OpenAI$2.5 / 1M tokens
BModel B
Google$0.1 / 1M tokens
Answer Relevance
GPT-4o wins
GPT-4o
92%
Gemini 2.0 Flash
87%
Context Faithfulness
GPT-4o wins
GPT-4o
90%
Gemini 2.0 Flash
82%
Hallucination Ratelower = better
GPT-4o wins
GPT-4o
3%
Gemini 2.0 Flash
7%
Latency p95lower = better
Gemini 2.0 Flash wins
GPT-4o
820ms
Gemini 2.0 Flash
310ms

93%

Quality B delivers vs A

4%

Cost of B vs A

$672

Est. monthly saving (B vs A)

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Expert Insight

For RAG pipelines, answer relevance and faithfulness matter most. Choosing the wrong model can result in 3× more hallucinations , an invisible quality drain that erodes user trust.

Scores are indicative benchmarks based on published evaluations. Real-world results vary by workload , that's exactly why we run workload-specific assessments.

Application Strategy

Zero Waste. Maximum Output.

The right model for one task is the wrong model for another. We map your workloads to the models that deliver the best quality-to-cost ratio , not the most impressive benchmark scores.

🔍

Internal Search & RAG

Your teams run hundreds of searches a day. Every hallucinated answer or irrelevant result is a hidden cost , in wasted time, wrong decisions, and escalations.

Up to 42% cost reduction
📄

Data Extraction

When you're processing thousands of documents, small error rates compound fast. We benchmark extraction accuracy and schema compliance across models.

Up to 38% cost reduction
✍️

Creative Content

Creative generation and multi-step reasoning is where most teams overspend. Quality gaps between premium and mid-tier models are often marginal.

Up to 61% cost reduction
💬

Customer Support

AI-assisted support bots handle thousands of tickets. Resolution rate, empathy, and escalation rate directly impact customer satisfaction and support headcount.

Up to 44% cost reduction
💻

Code Generation

Copilots and internal dev tools live or die on correctness. A model that produces plausible but buggy code is more dangerous than no model at all.

Up to 35% cost reduction
📑

Document Summarization

Legal, financial, and research teams summarize thousands of documents. Factual consistency and conciseness are non-negotiable , hallucinations in summaries cause real risk.

Up to 55% cost reduction

Your Estimated Annual Savings

Based on average enterprise AI spend across these workloads.

Internal Search & RAG$70,560 / yr
Data Extraction$95,760 / yr
Creative & Reasoning$69,540 / yr
Total potential saving$235,860 / yr

Median outcome across assessed clients. Actual results vary.

Get My Custom Estimate

Who We Work With

Precision Evaluation for Every Leader

Whether you own the budget, the quality bar, or the roadmap , BlanEval speaks your language.

CTO / VP Engineering

"Are we getting value from our AI budget?"

Clear cost-per-quality benchmarks. Defensible build-vs-buy decisions. Infrastructure spend tied to measurable outcomes.

Head of QA / AI Quality

"How do we actually measure LLM output quality?"

Automated evaluation frameworks. Reproducible test sets. Regression detection before production.

Product Owner

"Will users notice if we switch models?"

Side-by-side user-facing quality comparisons. Clear go/no-go signals. Fast iteration without risk.

CIO / Procurement

"How do we justify AI vendor spend?"

Vendor-neutral benchmarking. Documented evidence for procurement decisions. Ongoing cost monitoring.

50+

Agents Audited

40%+

Avg Cost Saving

100%

Quality Assurance

10k+

Evals Performed

Free Engagement

Book Your Ecosystem Assessment

We audit your current AI stack, benchmark your models against your actual workloads, and hand you a clear optimisation roadmap.

  • Full audit of your current AI stack & spend
  • Model-level quality benchmarks for your actual use cases
  • Prioritised list of optimisation opportunities
  • Written recommendation report delivered within 5 business days

No commitment required. Your data is kept confidential.