How Does Valley's AI Message Personalization System Work?
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Does Valley Use Multiple AI Models to Create Messages?
Valley employs seven different specialized LLMs working in concert to create each message, not just a single AI model. This sophisticated orchestration includes GPT-5, Claude Sonnet 4.5, Gemini 2.0, Jurassic, and other models, with each handling specific tasks. One model analyzes structural details, another handles contextual relevance, a third manages word choice and slang, while others focus on grammar preferences, tone matching, and LinkedIn-specific optimization.

This multi-model approach prevents the generic "AI voice" that plagues single-model systems. As Valley experts explain, each model has a separate task, creating a long network of LLMs stringed together that ensures messages sound genuinely human rather than AI-generated.
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How Deep Does Valley's Prospect Research Actually Go?
Valley conducts 15-30 pages of research per prospect, pulling from over 100 different data points across the entire web. The research spans LinkedIn profiles, entire company websites (every page indexed), social media presence across TikTok, Instagram, YouTube, and Spotify, podcast appearances and speaking engagements, press releases and news mentions, hiring trends from job postings, funding history and investor information, and even Reddit discussions related to the company or industry.

Valley's research agents include options like Company Deep Dive (capturing employee count, organizational structure, revenue, growth rate), Financial Performance (pulling from 10Ks, earnings calls, public financials), Industry News and Deep Dive, Press Releases, and Recent News. Users select five research agents per campaign from 25 available options, creating a Netflix-styled algorithm of information gathering.
Can Valley Learn and Replicate Your Unique Writing Style?
Valley's writing style system goes far beyond simple tone settings. The platform learns your communication patterns through multiple inputs: examples of successful messages you've written (the more the merrier, but even 3-5 examples work), specific dos and don'ts for communication, industry-specific terminology and phrases, and structural preferences like how you end messages or include CTAs.

Users can load examples directly into the platform, and Valley will deduce writing style focusing on word choice, slang, grammar preferences, sentence structure, and even punctuation patterns. Whether you prefer formal business communication or casual conversational tones, Valley adapts to match your authentic voice. The system even handles multiple languages, with German and French being particularly popular among Valley's 300+ customers.
How Does Valley Ensure Messages Don't Sound AI-Generated?
Valley employs multiple techniques to ensure authentic-sounding messages. First, the seven-model architecture prevents repetitive patterns that plague single-model systems. Each message is built from scratch based on specific prospect research, not modified from templates. Valley incorporates natural variation in message structure, length, and style - sometimes leading with questions, sometimes with observations, sometimes with connection points.
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The platform uses grammatically imperfect CTAs intentionally to sound more human. Valley avoids AI tells like excessive exclamation points, overly formal language, or generic transitions. Users consistently report that prospects can't tell messages are AI-generated, with many stealing Valley's messaging for their manual outreach.
What Research Agents Should Valley Users Select for Different Industries?
Research agent selection dramatically impacts message quality.
For technical buyers, prioritize Hiring Trends (identifies tech stack from job postings) and Company Deep Dive (architecture details).
For executives, focus on Fundraising History and Press Releases for strategic initiatives.
For operations roles, emphasize Financial Performance and Market Share data.
Valley allows customization through writing style instructions. One airline industry client instructed Valley to focus on new routes and destinations - after adding this rule, every research report included 15+ relevant articles on that topic. Users targeting banks successfully used Financial Performance agents to reference specific numbers from 5300 reports, creating highly relevant personalization.
How Does Valley Handle Prospects with Limited Online Presence?
Even for prospects with minimal LinkedIn activity or sparse digital footprints, Valley finds personalization angles. The platform looks beyond individuals to examine company-level signals, industry trends, competitive landscape, and peer company activities. Valley might find prospects quoted in trade publications, mentioned in company blogs, or listed in conference rosters.
For truly minimal-information prospects, Valley uses intelligent company and industry-level personalization. Rather than generic messages, it references recent company initiatives, industry challenges, or competitive dynamics relevant to someone in that role. Valley can even pull from Reddit discussions about the industry or company, though linking specific Reddit profiles to individuals remains challenging.
Can Valley Personalize Messages in Multiple Languages?
Valley successfully operates in approximately 20 different languages, with particularly strong capabilities in German, French, and Spanish. The system doesn't translate - it writes natively in each language. Users load examples in their target language, and Valley captures linguistic nuances including regional dialects, local expressions, and cultural communication patterns.

For Canadian French versus France French, Valley adapts based on the examples provided. German customers report excellent results, with over 10 active German-language customers. The key is providing all training information in the target language, including specific dialects, phrases, abbreviations, and contractions you want to use.
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