The Challenge
Revenue teams are drowning in data but starved for insight
CRM hygiene, forecasting accuracy, and rep productivity gaps compound into missed quota quarter after quarter.
Lead Scoring at Scale
Marketing hands off thousands of leads with minimal qualification. Sales reps spend 60% of their time on leads that will never convert, while high-intent prospects go un-followed-up.
Forecast Inaccuracy
Pipeline forecasts derived from rep-entered CRM data are systematically optimistic. Deal stage definitions are inconsistently applied, and deal risk signals go undetected until it's too late.
Rep Time on Admin
Sales reps spend 28% of their time on data entry, email follow-up, and CRM updates. Every hour of admin is an hour not spent in front of customers.
Deal Coaching at Scale
Sales managers can only review a fraction of calls and deal activity. High-risk deals and coaching opportunities are invisible until missed quarter-end.
Education AI Solutions
AI systems for sales, revenue operations, and GTM
Lead Scoring & Prioritization
ML models trained on your historical win/loss data that score inbound and outbound leads by conversion probability, directing rep attention to the highest-value opportunities.
Pipeline Forecasting AI
AI forecasting that analyzes deal engagement signals, email response rates, and stage progression velocity to produce more accurate revenue predictions than CRM-based rollups.
AI Sales Assistant
LLM-powered assistant that drafts follow-up emails, surfaces relevant case studies, generates call prep briefs, and logs CRM updates from call transcripts automatically.
Deal Risk Detection
AI that monitors engagement signals, champion activity, and deal progression to surface at-risk deals 3–4 weeks before they slip, triggering manager coaching interventions.
Competitive Intelligence
Real-time monitoring of competitor moves, pricing changes, and win/loss patterns, synthesized into updated battlecards and objection-handling guidance for reps.
Territory & Quota Optimization
AI analysis of market potential, rep capacity, and historical performance to recommend optimized territory assignments and quota allocations for the new fiscal year.
End-to-End Implementation
End-to-end AI implementation for sales & revenue
Solnix delivers the full lifecycle, from opportunity mapping through production deployment and continuous improvement. The same proven methodology powers every sales & revenue engagement, tailored to your systems, data, and workflows.
Discovery & AI Opportunity Mapping
We start by understanding your operations, data landscape, and goals, then map where AI delivers measurable value and where it does not. Every engagement begins with a prioritized opportunity backlog, not a technology pitch.
Data Foundation & Readiness
AI is only as good as the data behind it. We assess data quality, connect fragmented sources, and build the secure, governed pipelines that production AI depends on, with privacy and compliance designed in from the start.
Model & Agent Development
We build the models, retrieval systems, and AI agents tailored to your use cases, selecting the right approach (fine-tuning, RAG, multi-agent orchestration) for accuracy, cost, and latency, and validating against your real-world edge cases.
Integration & Workflow Embedding
AI only creates value when it lives inside the tools your teams already use. We embed models and agents into existing systems, surfaces, and workflows, so adoption is natural and human-in-the-loop controls stay in place.
Deployment, Security & Compliance
We deploy to production with the security, monitoring, and compliance controls enterprises require, including bias and fairness testing, audit logging, and the observability needed to operate AI responsibly at scale.
Optimization & Continuous Improvement
AI systems improve with use. We measure outcomes against the goals set in Phase 01, retrain and tune from live feedback, and expand to the next set of use cases, turning a single deployment into a compounding capability.
Methodology
How Solnix Builds Sales AI
01, CRM & Data Audit
01, CRM & Data Audit
We assess your CRM data quality, deal history, and signal coverage, establishing a baseline for model training and identifying the data enrichment needed to support reliable AI.
02, Win/Loss Model Training
02, Win/Loss Model Training
Sales AI models are trained on your historical opportunity data, not generic industry data. We require a minimum of 6 months of closed deals to build reliable prediction models.
03, CRM Integration
03, CRM Integration
AI outputs are delivered within Salesforce, HubSpot, or your CRM of choice, as scores, alerts, and recommended actions within existing rep workflows.
04, Rep Onboarding & Adoption
04, Rep Onboarding & Adoption
Sales AI only creates value if reps trust and use it. We run structured adoption sessions with sales teams and measure behavioral adoption alongside output metrics.
05, Quota Cycle Calibration
05, Quota Cycle Calibration
Forecasting models are recalibrated at each quarter start against actual results. We build the feedback loop that makes the model more accurate with each pipeline cycle.
FAQ
Questions from CROs, RevOps leads, and sales VPs
Get Started
More Pipeline. Better Forecast. Higher Win Rate.
Solnix builds sales AI that gives revenue teams the information advantage to forecast accurately, coach proactively, and close more efficiently.
Request a Sales AI Assessment →