we are an ai-native
Sales Performance &
Enablement Studio

Change log

1.0, October 8, 2025: Initial publication of Sales Rocket AI transparency and use policy.

How does Sales Rocket use AI?

We are an AI-native agency. This page explains how we use AI to accelerate growth while protecting your data and your brand.

What does AI do for our clients?

Humans remain accountable for all client outcomes. AI assists research, drafting, and analysis. We make the final call. Examples of where we help clients implement AI systems:

  • Prospecting at scale: enrichment, list building, ideal customer profile matching, territory and account planning.

  • Messaging that lands: sequence drafting, subject-line testing, call and demo summaries that feed follow-ups.

  • Pipeline intelligence: objection clustering, next best action suggestions, deal risk signals, forecast support.

  • Content at speed: ad variations, landing page copy tests, sales collateral personalization.

  • CRM hygiene: contact deduping, note extraction, activity tagging, field validation.

  • Sales ops automations: routing, SLA alerts, meeting prep, and briefings.

How DO we label our work?

Clear labeling helps everyone understand where and how AI contributed.

  • Human Generated, Human Approved

  • Co-Created with AI, Human Approved

  • AI Generated, Human Approved

  • AI Generated for low-risk automations such as guided chatbots or internal summaries

This structure follows a simple, visible framework inspired by industry transparency pages that distinguish human-authored, human-reviewed, and automated outputs.

What guardrails do we use?

  • Human oversight: specialists review AI-assisted work for accuracy, tone, and brand fit.

  • Quality data: we use curated, permissioned sources to reduce the risk of hallucinations and the introduction of undesired bias.

  • Rigorous review: spot checks, peer review, and automated QA before anything goes live.

  • Team training: ongoing enablement on prompts, evaluation, and safe use.

How do we protect your Privacy and security?

  • Your CRM and PII never become public training data, period.

  • When we use third-party models, we select enterprise tiers with data controls or route through gateways that disable training on your content.

  • Access is least privilege. Logs are retained only as long as needed for delivery and auditing.

If you prefer that no external models touch your data, tell us, and we will use approved private models or on-platform features.

What models and tools do we use?

We work with a mix of large language models and task-specific models for classification, summarization, entity matching, and generation. Tools include prompt orchestration, RAG over your content, analytics layers for evaluation, and connectors for CRM, ads, and support platforms. Exact vendors may vary by client requirements, data residency, and security reviews.

What are the Known limitations of AI?

AI can miss nuance or infer patterns from imperfect data. We avoid high-risk automation without human review, we monitor for bias and drift, and we welcome client feedback.

Are we open to feedback about AI Usage?

Transparency is a practice, not a page. We publish changes here, invite questions, and encourage feedback on any AI-augmented deliverable. This mirrors open dialogue and regular update commitments seen in responsible AI disclosures.

Where do we use AI in Sales workflows?

  • Research accounts, surface buying groups, enrich contacts, and flag trigger events.

  • Draft first pass outreach, tailor value props, generate call briefs and talk tracks.

  • Suggest channels and timing, adapt tone to persona, propose follow ups after calls.

  • Summarize multithreaded threads, map objections to proof points, produce mutual action plans.

  • Aggregate insights, forecast win probabilities , and highlight opportunities to accelerate.