Solving the
LLM Customization Problem

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Stages of LLM Customization

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Launch Readiness Evaluation

Enterprise-specific dimensions

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Synthetic Data Generation

Instructions and Preferences

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Alignment Fine-tuning

Open Source and Enterprise models

Make your LLMs reliable by creating launch criteria judge

Safety

Prioritize safety and brand alignment

Truthfulness

Maintain Factual Accuracy and Consistency

Brand Alignment

Leverage your Tone and Style

Unparalleled Business Metrics

Accelerate your ROI 8x (from 6 months to 3 weeks) using an end-to-end alignment solution

Time to Market

~18X more cost-efficient compared to buying human-curated data

Cost to Market

Optimize your Launch Readiness

with Collinear AI's superior fine tuning with minimal annotations versus competitors
Create launch criteria evals for your Task

No more generic LLMs that are not correlated with your data. Train a LLM-as-a-judge on your custom launch criteria using handful of annotations and use it to judge hundreds of responses at scale. It can also be used to judge preferences for feedback fine tuning.