Expert-in-the-Loop services for Gen-AI
Code Evaluation, Prompt Engineering, and Red Teaming to make AI safer, smarter, and enterprise-ready.
© 2035 by leadmaven.in
Frequently Asked Questions
Q1. How quickly can you start?
Pilots can start within a week (subject to access and data readiness).
Q3. How do you measure quality?
Rubrics with weighted criteria, IRR tracking, precision/recall for defect classes, SLA dashboards.
Q5. Can you handle both small pilots and large-scale ongoing projects?
Yes. We start with focused pilots (1–2 weeks) to align on rubrics and workflows, and can quickly scale up dedicated pods of experts for high-volume, ongoing needs.
Q2. Which languages do you support?
Python, Java, JS/TS, C/C++, Go, SQL (and more on request).
Q4. Can you use our internal tools?
Yes—most customers prefer we work inside their environments with SSO
Q6. How flexible are your engagement models?
We offer multiple options—per-task, hourly, or dedicated monthly pods—so you can choose a model that matches your budget and project scale without sacrificing quality.
Expert reviewers + multi-tier QA for reliable judgments.
Accuracy at Scale
Measurable improvements to safety, compliance, and enterprise policies
Model Integrity
Engineers & SMEs across software, data, security, & education (STEM)
Domain Expertise
Tight feedback loops shrink training/eval cycles.
Faster Iteration
Your schemas, your tools, your SLAs
Flexible Workflows
Transparent, flexible pricing that adapts to your project needs without enterprise markups
Competitive Pricing
Engagement Models
Pilot
Fixed-scope 1–2 weeks to align on rubrics, outputs, and metrics
Managed PODs
Dedicated evaluators with lead + QA; monthly throughput targets
Burst Capacity
On-demand surge teams for launches or retraining cycles
BOT
We assemble and train; you internalize when ready
How it Works
Define tasks, languages, eval rubrics, pass criteria, and SLAs.
Scope & Metrics
1
1–2 week pilot; align on rubrics, inter-rater reliability, and reports.
Pilot & Calibrate
2
Elastic teams, SOPs, and dashboards; hit throughput & quality targets.
Scale Production
3
Weekly insights, error taxonomy, prompt refinements & safety tests.
Continuous Improvement
4
100+
Expert Evaluators
1M +
Code Results Reviewed
95%+
QA Accuracy
<24h
Turn Around Options
Why Companies Choose Us
Proven Impact
LLM Safety Team
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Need: Stress-test for jailbreaks + leakage.
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Approach: Red-team suite with seeded exploits & continuous regression.
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Outcome: 60% reduction in successful jailbreak patterns quarter-over-quarter.
EdTech Evaluations
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Need: Consistent grading for student code + feedback clarity.
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Approach: Prompt redesign + structured hints, partial-credit rubric.
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Outcome: 22% higher learner satisfaction; faster resolution times.
AI Data Platform
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Need: Validate 100k+ code generations/month across 6 languages.
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Approach: 40-person EITL pod, test cases + scoring schema, weekly error taxonomy.
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Outcome: 95%+ rubric adherence; 28% drop in critical errors in 6 weeks.
What Customers Say
A few words from our clients.
“The red teaming suite they developed uncovered vulnerabilities our internal team had missed. Their adversarial prompts and continuous regression testing made our model much more resilient.”
Head of Safety, LLM Lab
“We were struggling with inconsistent grading from our automated systems. The EITL team refined prompts, built rubrics, and ensured human validation. Our learner satisfaction scores jumped significantly.”
VP of Product, EdTech Startup
“Their expert-in-the-loop reviewers became an extension of our own engineering team. Code eval accuracy went up, release cycles sped up, and we finally had the confidence to scale our copilots.”
Director of AI Engineering, Global Platform