Your AI is working.
But is it actually right?

AI, data evaluation and analytics work

No synthetic AI presented as human judgement

Direct practitioner involvement end to end

India-based, globally serving

/ 01 / WHAT WE TAKE ON

1/. AI works in the demo, but production behavior is uncertain.

2/. The evaluation suite passes, but important failures still appear

3/. A live AI system is useful, but nobody can state its quality clearly.

4/. One internal expert is the only person who can say whether an answer is right.

/ 02 / EVALUATION SCOPE

We independently evaluate autonomous agents, enterprise retrieval architectures, and end-to-end AI workflows using production stress tests, human validation, and empirical metrics.

AI Agents

RAG Systems

LLM Applications

Testing autonomous decision chains, multi-tool execution, safety guardrails, and deterministic fallback paths under complex real-world operational conditions.

Evaluating a RAG system's performance by measuring retrieval accuracy, contextual grounding, LLM hallucination rates, and source attribution precision across proprietary knowledge bases.

Evaluating prompt robustness, output consistency, complex edge-case handling, and deterministic task completion for mission-critical software.

Voice AI

Document AI

AI Workflows

Assessing real-time audio latency, natural turn-taking dynamics, speech recognition accuracy, and conversational recovery logic in live settings.

Measuring key-value extraction precision, complex tabular data parsing, visual layout comprehension, and structured schema compliance.

Validating end-to-end multi-agent orchestration, human-in-the-loop handoffs, exception handling, and enterprise system resilience.

/ 03 / WHAT YOU RECEIVE

Custom evaluation methodology tailored specifically to your LLM architecture, autonomous agent workflows, and operational edge cases.

Structured evaluation assets, comprehensive benchmark data, and complete audit trails so your engineering and leadership teams can independently verify model performance and safety.

Curated adversarial prompt suites, edge-case test vectors, and gold-standard verification datasets with full metadata annotation.

Deterministic evaluation logic combined with structured human-in-the-loop scoring matrices for accuracy, toxicity, and hallucination bounds.

Quantitative metrics and comparative performance ratings against task completion baselines, latency bounds, and precision standards.

Granular classification of model breakdowns, vulnerability patterns, system prompt leaks, and root-cause diagnostic records.

Executive summary alongside full technical audit documentation, highlighting key risks and prioritized mitigation steps.

/ 05 / ADDITIONAL CAPABILITIES

While independent evaluation and human assurance form our primary mission, Axe Network continues to provide specialized technical execution across high-demand AI workflows.

Document Intelligence

AI / LLM Annotation & RLHF

Property & Enterprise AI

Automated extraction, key-value parsing, and structured data validation for complex unstructured documents, PDF forms, and corporate records.

Specialized AI solutions tailored for real estate analytics, property operations, and enterprise workflows requiring audited domain logic.

High-accuracy human feedback, domain-specific instruction tuning datasets, and RLHF alignment pipeline execution built by expert evaluators.

Evaluation Triggers

Demo vs Production

Blind Automated Metrics

High-Stakes Workflows

Governance & Compliance

AI works reliably in controlled demos, but real production user behavior produces unpredictable responses and systemic edge-case failures.

The internal benchmark suite passes green, yet critical real-world edge cases continue failing quietly in active production workflows.

Critical domain processes require strict human verification and ground truth validation before scaling deployment company-wide.

Enterprise risk, audit controls, and regulatory governance demand verifiable proof and documented evidence for AI decision paths.