We are excited to announce our $2M seed round led by Joa Capital.
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Of the B2B buying decision is complete before a prospect ever contacts a vendor directly.
Average wasted ad spend per quarter from campaigns that aren't optimized based on real-time signal feedback.
Improvement in campaign ROI when brands optimize messaging based on real-time consumer sentiment vs. post-campaign analysis.
Real-time feedback on message resonance and channel effectiveness. See which creative spreads organically, which falls flat—pivot mid-flight.
Demographic signal clustering by age, gender, income, profession. Segment audiences showing highest intent and engagement quality.
Map which platforms, groups, and communities your target audience inhabits. Track influencer networks and conversation amplifiers.
Supervised ML model trained on 2M+ labeled buying journey conversations. Classifies mentions into discrete stages (Problem-Aware → Solution-Explore → Vendor-Compare) using linguistic pattern recognition and contextual entity analysis. 89% stage precision.
Entity resolution algorithms aggregate individual mentions to company-level intelligence. Fuzzy matching on email domains, LinkedIn profiles, and IP-to-company reverse lookup with 92% identification accuracy. Tracks buying committee multi-person signals.
LSTM neural networks model behavioral trajectory at individual consumer level. Predicts conversion likelihood based on engagement pattern evolution, sentiment shifts, and content interaction sequences.
Cross-platform attribution engine with signal velocity correlation analysis. Measures campaign message propagation speed, organic amplification rate, and engagement quality—generating lifecycle impact scores (0-100).
Graph-based centrality analysis using eigenvector algorithms to identify high-authority nodes in conversation networks. Ranks influencers by reach, engagement quality, and audience relevance—not just follower counts.
