AI Product Development Company
Turn an AI prototype into a real SaaS product with auth, billing, multi-tenant infrastructure, and deployment.
Explore AI Product DevelopmentSalesight.ai scores every sales call against your playbook and delivers coaching automatically. No more sampling 10%. No more subjective reviews. Built by BrownMind in collaboration with Ante Digital in Canada.
Manual call review creates blind spots that cost you deals, coaching quality, and rep performance.
Managers pick a handful of calls to review each week. The other 90% go unexamined — bad habits compound in silence.
Feedback depends on who's reviewing. One manager focuses on discovery, another on objection handling. No shared standard.
You built a sales playbook, but nobody can verify whether reps actually follow it. Compliance is a guess.
As your team grows, the review bottleneck gets worse. You can't hire reviewers fast enough to keep up with call volume.
Define your scoring criteria. The system embeds your playbook as vectors for semantic evaluation.
Fathom, Fireflies, or direct webhooks. All sources normalize into a unified pipeline automatically.
Every call is scored against your playbook. Reps get actionable coaching. Managers get dashboards.
Watch how Salesight.ai processes calls, scores against your playbook, and generates coaching in real time.
Built for 100 orgs, not just yours. This isn't a prototype.
Your playbooks don't leak to other teams. Each org is a sealed environment — separate users, separate limits, separate everything.
Your playbook gets embedded and retrieved at scoring time. Every evaluation cites the specific criteria it's grading against.
Calls get analyzed in the background. If something breaks, it retries automatically. You don't babysit it.
Stripe handles subscriptions. Each org has usage limits and budget controls. No surprise invoices.
Fathom, Fireflies, or direct uploads. One pipeline normalizes everything with dedup and validation.
Feedback flows to Slack, Discord, or email. Your team sees it without logging into another dashboard.
Sales calls reviewed manually — slow, subjective, impossible to scale
AI evaluates every call against custom playbooks and delivers coaching automatically
Coaching quality varied wildly between reviewers with no shared standard
Consistent, playbook-grounded scoring across every team using RAG-based evaluation
Transcripts arrived from multiple sources with no unified processing
Single ingestion layer normalizes all sources into a shared format with dedup
No usage billing or budget controls — LLM costs unpredictable as volume grew
Stripe-synced tiered billing with per-organization usage limits and budget controls
Turn an AI prototype into a real SaaS product with auth, billing, multi-tenant infrastructure, and deployment.
Explore AI Product DevelopmentSee the multi-tenant sales coaching product we shipped with RAG, billing, org isolation, and production observability.
Read the SaaS Case Study