Choosing the right AI models is critical to delivering high-quality outbound at scale. Here's how we evaluate and deploy different models across our pipeline.
Our Multi-Model Approach
We don't rely on a single AI model. Different tasks require different capabilities:
Research & Analysis: Claude
For deep company research and signal analysis, we use Anthropic's Claude models. Claude excels at synthesizing information from multiple sources, understanding business context, and producing structured analysis.
Email Generation: Custom Fine-Tuned Models
For writing emails that convert, we use custom models fine-tuned on millions of successful outbound sequences. These models understand the nuances of B2B communication.
Quality Scoring: Specialized Classifiers
Before any email is sent, it passes through our quality scoring pipeline — smaller, specialized models that evaluate personalization depth, tone appropriateness, and deliverability factors.
Benchmarking Results
We continuously benchmark our models against alternatives:
- Response rate: Our fine-tuned models achieve 35% vs 12% for generic GPT-4
- Personalization score: 92% of emails rated as "deeply personalized" by human reviewers
- Tone accuracy: 97% match to target brand voice
The Future
As foundation models improve, we're exploring multi-modal approaches that incorporate voice and visual signals for even deeper prospect understanding.
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