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v9ai/salescue-reply-v1

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SalesCue — reply

ReplyHead module from the SalesCue sales intelligence library.

Status: untrained — architecture only, random initialization. Use as a starting point for fine-tuning.

Research Contribution

Constrained CRF for Structured Reply Classification

Multi-label classification treats labels independently, but reply labels have structural constraints: unsubscribe and genuinely_interested are mutually exclusive; referral implies not_now. ReplyHead enforces these via a constrained conditional random field where the transition matrix encodes label co-occurrence rules.

Usage

python
from salescue import SalesCueModel

model = SalesCueModel.from_pretrained("v9ai/salescue-reply-v1")
result = model.predict("your sales text here")
print(result)

Labels

  • —genuinely_interested
  • —politely_acknowledging
  • —objection
  • —not_now
  • —unsubscribe
  • —out_of_office
  • —bounce
  • —meeting_request
  • —referral
  • —negative_sentiment

Architecture

  • —Backbone: `microsoft/deberta-v3-base` (shared encoder, 768-dim)
  • —Head: ReplyHead
  • —Parameters: head only (backbone loaded separately)

Intended Use

  • —Primary: B2B sales intelligence — lead scoring, email analysis, conversation insights
  • —Users: Sales teams, RevOps, GTM engineers building sales automation
  • —Input: English sales text (emails, call transcripts, prospect communications)

Limitations

  • —Untrained weights: This release contains the architecture only. Weights are randomly initialized and must be fine-tuned on domain-specific data before production use.
  • —English only: Designed for English sales text. Performance on other languages is untested.
  • —Domain-specific: Optimized for B2B sales communications. May not generalize to other text domains.
  • —Shared backbone: Requires microsoft/deberta-v3-base loaded via the SalesCue library.

About SalesCue

SalesCue is a sales intelligence library with 12 ML modules sharing a single DeBERTa-v3-base encoder backbone. Modules can be composed via Unix-style piping:

python
from salescue import Document
result = Document("interested in pricing") | ai.score | ai.intent | ai.sentiment

All modules: score intent reply triggers icp objection sentiment spam entities call subject emailgen

See the SalesCue documentation for details.