Not a chatbot demo. Not an AI strategy deck. A structured adoption program that turns AI tools into measurable revenue improvements — with a framework built from how top-performing sales organizations actually use AI.
Tools are getting adopted. Dashboards are getting built. But measurable revenue impact remains elusive for most teams — because they're implementing tools without a system.
Four phases. Built in sequence. Each one required for the next to work. ARIA is designed around the failure patterns we see most: companies that skip Assess and go straight to tools, or who Implement without a Roadmap.
Current state audit of AI tool usage, data infrastructure readiness, workflow integration gaps, and team capability. Produces an AI Readiness Score across five dimensions and a prioritized gap map.
"No recommendation before we understand what's there."
Use-case prioritization using a leverage × effort matrix. Every potential AI application is scored on revenue impact and implementation complexity. We find the 20% that delivers 80% of the value — and sequence it into 30-day blocks.
"The leverage map, not the wishlist."
Tool selection, integration design, prompt engineering, team training, and full enablement. We do the build alongside your team — not a list of recommendations. Clients leave with configured tools and a trained team, not a PDF.
"We build it. We don't just advise on it."
Monthly KPI tracking sessions, tool performance reviews, prompt optimization, and expansion planning. AI adoption compounds over time — but only with a cadence that forces measurement and iteration built into the calendar.
"Adoption is a system, not an event."
These are the use cases with the highest leverage-to-effort ratio across B2B sales organizations — the 20% that reliably produce the 80%.
AI analysis of closed-won and closed-lost patterns to sharpen the ICP definition — who actually buys vs. who the team thinks buys.
Real-time deal health scores based on activity patterns, engagement signals, and historical win-rate indicators — replacing gut-feel pipeline reviews.
Automated monitoring of competitor moves, pricing changes, and messaging shifts — surfaced to reps before discovery calls, not after deals are lost.
Post-call analysis of recorded conversations — skill gap flagging, objection pattern analysis, and coaching recommendations delivered automatically to managers.
AI-generated first drafts for outbound sequences personalized to each prospect's industry, role, and recent signals — without requiring 45 minutes per rep per day.
Scoring territories by TAM density, market maturity, and rep skill match — replacing the annual gut-feel territory carve with a defensible, data-backed structure.
Visual mapping of where the highest-probability opportunities sit within each territory — so reps spend time where conversion likelihood is highest.
Automated analysis of accounts that haven't been touched in 60+ days, segments with no coverage, and rep bandwidth mismatches — before pipeline suffers.
Matching rep skill profiles to territory complexity using AI analysis of past performance data — improving quota attainment without changing headcount.
Automated flagging and correction of stale deals, missing fields, and stage inconsistencies — keeping the CRM accurate without adding to rep admin overhead.
Auto-generated weekly pipeline summaries, rep performance narratives, and forecast variance explanations — delivered to managers before Monday standup.
Real-time signals from G2, Bombora, and LinkedIn aggregated by account — triggering rep outreach when intent scores spike, not 30 days later.
AI-scored MQL routing, automatic context packets delivered to reps at handoff, and response-time tracking — eliminating the lead black hole.
Each deal in the commit category gets an AI confidence score based on activity, time in stage, and historical patterns — so forecast is defensible, not aspirational.
From a 48-hour readiness scan to a full 90-day transformation — sized to your company's stage and appetite for change.
Current state audit, AI Readiness Score, and a prioritized list of 3–5 quick-win use cases you can implement immediately — without a full engagement.
Readiness scan + first two use cases configured and deployed. Team trained. Measurement system in place. You leave with AI tools actually running — not just selected.
Full ARIA assessment through implementation. 4–6 use cases deployed across the sales function. Manager enablement included. KPI baseline and measurement cadence established.
End-to-end ARIA implementation across the full revenue organization. 8–12 use cases. Full team training. Adapt cadence built in. 70/30 fee structure applies.
AI advisory is credible only when the advisor actually uses AI in their own work. We do — every engagement is Claude-augmented, and that practice informs every recommendation we make.
Analysis that used to take 2 weeks now takes 2 days. That speed is passed directly to clients as lower cost and faster results. We're not advising on AI from theory — we're running it in production, every day.
Most AI consultants understand the technology. We understand the revenue system the technology is being applied to. That intersection — sales methodology + AI implementation — is where ARIA lives.
Every ARIA engagement includes hands-on configuration, prompt engineering, and team enablement. You don't leave with a list of tools to evaluate — you leave with tools running and teams trained.
30% of every AI engagement fee is held at the Day 90 KPI gate — tied to measurable outcomes, not just deliverable completion. If the AI implementation doesn't move the needle, we don't collect the gate.