Sales as the CONVERT stage — connected to Marketing's inbound flow, Customer Success's onboarding, and your existing CRM.
AI doesn't replace your salesperson. It removes everything from their job that isn't selling.
Your salespeople spend most of their week not selling. They're researching prospects, updating the CRM, drafting follow-ups, generating proposals, chasing forecasts. Roughly 70% of sales time is administrative. We automate that 70% — so the 30% that requires a human gets the full focus it deserves.
10 minutes. We diagnose where your sales motion is losing the most time and recommend the single workflow to graduate first.
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Why most "AI for sales" tools fail.
There are two failure modes that show up across every "AI for sales" tool that's been pitched to your team in the last 18 months.
The first is canned outreach. The vendor promises personalized cold emails at scale. What you actually get is mail merge with marginally smarter variable substitution. The prospect sees the pattern within three lines. Reply rates stay flat or get worse — because now the prospect has explicit evidence that this isn't a real person.
The second is awkward AI in the meeting itself. The vendor promises real-time coaching, meeting intelligence, automatic note-taking. What your team actually experiences is a bot that joins the call uninvited, a transcript full of mis-attributed quotes, and a CRM update that misses the actual buying signals. The salesperson ends up doing the work twice — once with the AI, once correcting what the AI got wrong.
Neither failure mode is about the underlying model. They're both about the same root cause: the system doesn't know your business, your prospects, your salesperson's actual voice, or your sales motion. So everything it produces is generic. And generic, in sales, is the same as worthless.
THE HUREKA APPROACH TO SALES
Every workflow runs on top of a connected Brain that knows your case studies, your salesperson's voice, your competitive positioning, the prospect's company history, and every previous interaction. The system isn't generating sales content. It's drafting what your salesperson would have written — if they had infinite time to research.
What we automate, in plain English.
Five workflow areas covering the full sales cycle from prospect research through closed-won. Each is a Lego block — independently buildable, independently measurable. Most clients start with one (usually post-meeting follow-up) and add the others as the first one pays for itself.
Pre-Meeting Research Briefs
Drafts a one-page brief on every prospect call before the meeting — delivered to the salesperson the night before. Includes the prospect's recent news, hiring patterns, public financials where available, the attendees and their roles, the pain point hypothesis grounded in the company's stage, and which case studies from your library are most relevant.
INSIDE THE WORKFLOW
- Calendar integration triggers brief generation 18 hours before any external meeting
- Company intelligence pulled from public sources, news, hiring data, funding signals
- Attendee research — role, tenure, LinkedIn presence, prior interactions with your company
- Pain point hypothesis generated from company size, stage, industry, and known signals
- Case study matching — the 2–3 most relevant from your library, with specific metrics highlighted
- Suggested talking points and questions for discovery
- Delivered as one-page PDF + email summary to the rep
TYPICAL RESULTS IN 90 DAYS
Reps walking into meetings knowing more than the prospect expects · Close rate improvement 15–25% · Discovery calls feel like consulting conversations · Senior prospects start commenting "you've done your homework"
Illustrative typical-range numbers from project case study material.
Meeting Execution Support
Captures the meeting accurately without joining the call uninvited or making the conversation feel surveilled. Transcribes, extracts action items, logs objections, updates the CRM, and surfaces buying signals the salesperson can act on after the call.
INSIDE THE WORKFLOW
- Recording integration with the meeting platform (Zoom, Teams, Meet) — only when the rep enables it
- High-accuracy transcription with proper speaker attribution
- Action item extraction (commitments made by both sides)
- Objection logging — categorized by type (budget, timing, authority, need)
- Buying signal identification (specific phrases, emotional inflection points)
- CRM update with structured data (stage progression, next steps, key topics)
- Post-call summary delivered to rep within 5 minutes of meeting end
TYPICAL RESULTS IN 90 DAYS
CRM hygiene improves dramatically · Reps stop double-entering data · Buying signals get captured (not lost) · Manager pipeline reviews shift from data-collection to coaching · Forecast accuracy improves measurably
Illustrative typical-range numbers from project case study material.
Post-Meeting Follow-Up
Drafts the post-meeting follow-up email in the salesperson's voice — same-day, within an hour of the meeting ending. References specific moments from the conversation, attaches the right materials, proposes concrete next steps, and books the next meeting if appropriate. The salesperson reviews, edits if needed, and sends.
INSIDE THE WORKFLOW
- Triggered automatically on meeting end (no rep action required)
- Voice match calibrated to the specific rep — formal vs. casual, length preferences, signature
- Content pulled from the meeting transcript — specific quotes, commitments, questions raised
- Materials selection from your asset library based on topics discussed
- Next step proposed with calendar link or specific action requested
- Draft delivered to the rep within 60 minutes of meeting end
- Send happens with one-click approval
TYPICAL RESULTS IN 90 DAYS
Post-meeting response rates improve 30–40% · Same-day follow-up rate goes from ~30% to ~95% · Prospects mention the speed and specificity in subsequent conversations · Deals progress to next stage 1–2 weeks faster
Illustrative typical-range numbers from project case study material.
Proposal Generation
Generates personalized proposals that mirror the prospect's specific language, pain points, and stated metrics. Pulls from the discovery conversations, the case studies that resonated, and your standard pricing/scoping framework. Reads like a senior salesperson spent four hours on it — except the system took fifteen minutes and the rep needs ten minutes to review.
INSIDE THE WORKFLOW
- Triggered when an opportunity reaches Proposal stage in the CRM
- Pain point synthesis from all prior meeting transcripts and notes
- Solution framing in the prospect's own language (not your jargon)
- Case study selection and specific metric highlighting
- Pricing configuration from your standard framework with prospect-specific scoping
- ROI projection based on their stated baseline metrics where available
- E-signature ready format with version control
TYPICAL RESULTS IN 90 DAYS
Proposal turnaround from days to hours · Win rate on proposals improves 10–20% · Proposal-to-close cycle compresses · Reps stop dreading the proposal phase
Illustrative typical-range numbers from project case study material.
Pipeline Management & Forecasting
Keeps the pipeline honest. Flags stale deals, surfaces deals stuck at the same stage too long, identifies win/loss patterns, and produces forecasts with confidence ranges instead of single-number guesses.
INSIDE THE WORKFLOW
- Pipeline hygiene monitoring — deals not touched in N days flagged for review
- Stage-stuck deal identification with recommended next actions
- Forecast generation with statistical confidence ranges (not optimistic single numbers)
- Win/loss pattern analysis — what's actually closing vs. what's actually stalling
- Commission and quota tracking with real-time visibility
- Weekly executive pipeline summary auto-generated with anomalies and recommendations
TYPICAL RESULTS IN 90 DAYS
Forecast accuracy improves 25–40% · Stalled deals get attention before they die · Reps spend less time on pipeline review meetings · Manager 1:1s become coaching sessions, not status updates
Illustrative typical-range numbers from project case study material.
Same prospect. Same product. Different outreach.
Below: what generic AI sales tools produce vs. what a context-aware system produces. Same hypothetical prospect, same model underneath — the difference is everything your system knows about your business and theirs.
Generic. Could be sent to anyone. Reply rate: 1–2%. Often goes to spam.
Specific. References the prospect's actual situation. Reply rate: 15–25% — and the prospects who reply are pre-qualified.
Sales doesn't start at the cold email and end at the close.
Marketing feeds you context. Customer Success inherits the deal. With a connected system, both happen automatically — and your salesperson never has to send another internal "FYI" email.
A prospect who engaged with marketing appears in your pipeline
When the prospect's name appears on your calendar, the pre-meeting brief surfaces the marketing history — what they downloaded, what they engaged with, which case studies are most relevant given their behavior. The rep walks in knowing this is a warm lead, not a cold one.
A deal closes and customer success picks up
Onboarding starts automatically with full context — pain points raised in discovery, success metrics committed to, the implementation timeline agreed in the proposal. The CS manager doesn't re-discover anything in kickoff. The customer experiences continuity.
A qualified opportunity stalls for 30+ days
The prospect drops into a qualified-stalled nurture — not a generic one. They get content matched to the specific objections raised in the sales conversation. If they re-engage, sales gets notified with the new context.
Where to start.
Five workflows is a lot. Most sales teams start with one — based on which sales problem is loudest — and graduate the rest as the first one pays off.
| If your loudest sales pain is… | Start here | Why first |
|---|---|---|
| We follow up too slowly after meetings — deals go cold | Post-Meeting Follow-Up | Tightest feedback loop (results in week 1); easiest team buy-in |
| Our reps walk into meetings cold; discovery feels generic | Pre-Meeting Research Briefs | Visible quality lift on every call; reps love it |
| CRM is a mess; nobody updates it; the forecast is fiction | Meeting Execution Support | Automates the data entry tax; CRM hygiene fixes itself |
| Proposals take days to write; momentum dies in the proposal phase | Proposal Generation | Compresses the longest pause in your sales cycle |
| We can't tell which deals will close until they don't | Pipeline Management & Forecasting | Cross-cutting; makes every other workflow measurable |
The Audit's job is to figure out which row applies to your sales motion. Not to sell you the full system. To tell you which workflow to graduate first — and which to wait on until that one pays for itself.
Tools we connect to — not replace.
CRM
HubSpot · Salesforce · Pipedrive · Zoho · Copper · Microsoft Dynamics 365 · Close
OUTREACH TOOLS
Apollo · Outreach · Salesloft · Lemlist · Smartlead
MEETING PLATFORMS
Zoom · Microsoft Teams · Google Meet · Gong · Chorus
CALENDAR
Google Workspace · Microsoft 365 · Calendly · Chili Piper
LEAD DATA
Apollo · ZoomInfo · LinkedIn Sales Navigator · Clay · Lusha
PROPOSAL / E-SIGNATURE
PandaDoc · DocuSign · HelloSign · Better Proposals · Qwilr
Your CRM stays. Your outreach tool stays. Your meeting platform stays. The Brain connects them — and adds the intelligence layer that was missing.
What this looks like for a B2B SaaS company.
A typical engagement timeline for a mid-market B2B SaaS — 35 employees, $8M annual revenue, sales-led growth motion. Names withheld pending case study publication.
WEEK 1-4
Audit + Strategy Memo + Phase 1 setup
WEEK 5
Post-Meeting Follow-Up live — response rates up 40% within the first month
WEEK 7
Pre-Meeting Research Briefs added — close rate improved 18% on opportunities receiving briefs
WEEK 9
Customer Success: Churn risk scoring added — 8 at-risk accounts identified, 6 saved
WEEK 11
Customer Success: Automated QBR scheduling — completion rate from 40% to 92%
WEEK 14
Marketing: Blog content creation added — organic traffic up 35% in 90 days
WEEK 17
Customer Support: Tier 1 auto-response added — ticket volume to humans cut 55%
WEEK 20
Finance: Auto-invoicing on deal close — invoice cycle from 5 days to same-day
The pattern is worth noticing. They didn't roll out "AI for Sales." They started with the one Sales workflow that was hurting the most — post-meeting follow-up — and shipped it in week five. Pre-meeting briefs came in week seven. By week nine, the success of those two Sales workflows funded the first Customer Success workflow. By week twenty, they had seven workflows running across five functions — and each new workflow cost roughly 30% of what the first one cost, because the Brain had already been built.
Named SaaS case study in production. Will be linked here when published.
Common questions about Sales AI.
The opposite, in our experience. The system removes the parts of the job they already hate — CRM updates, follow-up writing, proposal drafting, pipeline reviews. The parts they love — talking to customers, closing deals — get the full focus. Within a month, most teams ask for more workflows rather than resist the ones that exist.
Three ways to take the next step.
Pick the level of engagement that fits where you are. On this page, the AI Audit is highlighted — because its specific job is to tell you which sales workflow to graduate first.
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10 minutes. We diagnose your sales motion and recommend the specific workflow to graduate first. 1-page Strategy Memo in 48 hours.
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30 minutes with Roopak. For sales leaders ready to talk specifics about which workflow to start with.
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