One system across the top of the funnel: AI-drafted outbound and reply handling, predictive lead scoring and pipeline reporting, quote and proposal drafting, and the CRM hygiene that keeps all of it honest. Not five point tools duct-taped together — one engine, monitored, and handed to your team to own.
Each part earns its place because it removes manual work from a rep's day — and because they compound when they share the same data and the same guardrails.
First-touch emails grounded in each prospect's public signals — not "Hi {firstname}." Warmed sending, sane volume, and an editor in the loop by default; full autonomy once your rules are stable.
Inbound replies read, categorized, and routed — meeting-ready ones surfaced, objections drafted for a rep to approve, out-of-office and unsubscribes handled quietly. Uncertain cases always go to a human with full context.
A fit-and-intent model trained on your actual closed-won data, not a vendor's generic template. Accounts get a score, reps see why, and the same signal feeds routing and forecasting — retrained on a cadence.
One source of truth for the weekly review — activity, stage velocity, forecast, and where deals actually stall. Reporting a founder or CRO reads without a training session, wired to your warehouse rather than invented beside it.
Once discovery notes and pricing rules are in place, the engine drafts first-pass quotes and proposals from your templates — right SKUs, terms, and deal context — so a rep edits and sends instead of starting from a blank page. A human approves every time.
Deduped records, enriched fields, normalized firmographics, and stale data flagged before it poisons a report. The unglamorous layer that decides whether every other part of the engine is working from truth or from noise.
Finyki's own new business comes from the same system we build for clients. It's the fastest proof we can offer: we're not selling a playbook we've only run on slides.
Our new-business pipeline runs on a warmed cold-sender on its own domain, send.finykidigital.com, kept separate from our primary identity so replies actually land. It writes personalized first-touch emails from a CRM sheet of ICP-lookalike accounts — deeptech, medtech, and B2B SaaS — at a deliberately sane cadence, with a human in the loop before autonomy is earned.
That's the point of this page: the outbound, reply handling, scoring, and CRM hygiene we sell are the same moving parts keeping our own calendar full. When we hand the engine to your team, we're handing over something we depend on — not a demo.
Shadow how outbound, scoring, and CRM updates happen today. Quantify the hours lost, find the dirty data, and pick the one slice worth automating first.
ICP definition, scoring signals, sending infrastructure, prompt architecture, and the CRM data contract. Warm the domain and stand up the eval set before anything sends.
First slice goes live behind an editor-in-the-loop gate — usually enriched, scored routing or an outbound sequence. Shadow-run against the manual process to prove outputs hold.
Reply handling, quote drafting, and reporting layer on as trust grows. Failure modes become eval cases; your team owns the loop, the logs, and the sending reputation.
“Replaced a 14-person AML triage team's workflow with the agent Finyki shipped. −71% triage time, audit-traceable end-to-end.”
Head of Risk · NDA, licensed payments platform · SG
A tool ships you an empty inbox and a template library. We ship a working system: warmed sending infrastructure, an ICP-scored account list, AI drafting grounded in each prospect's real signals, reply triage, and reporting wired to your pipeline. It's the same outbound engine we run on ourselves — configured for your team, then handed over to own.
Only if you let it. Every first-touch email is grounded in the prospect's public signals — not "Hi {firstname}." An editor stays in the loop by default, and the sender only earns full autonomy once your rules are stable. We warm the domain, keep volume sane, and separate cold sending from your primary identity so replies actually land.
No. We automate the research, drafting, scoring, CRM hygiene, and reporting that eat a rep's day — so the human time goes to the conversations that close. Uncertain replies and edge cases route to a person with full context, never a canned response.
We train a fit-and-intent model on your actual closed-won data, not a vendor's generic template. Accounts get a score and reps see why, not just what. It retrains on a cadence and lives in the warehouse, so the same signal feeds routing, reporting, and forecasting. This is the modeling side of our Data & RevOps Intelligence practice, pointed at the top of the funnel.
Yes. Once discovery notes and pricing rules are in place, the system drafts first-pass quotes and proposals from your templates — pulling the right SKUs, terms, and deal context — so a rep edits and sends instead of starting from a blank document. A human always approves before anything goes out.
A first working slice — usually enriched, scored routing or an editor-in-the-loop outbound sequence — is typically live in 2–3 weeks, shadow-run against your current process before it goes fully autonomous. The full engine builds out from there. See our pricing breakdown for how engagements are structured.
Tell us the one part of your sales motion your team is tired of doing by hand — prospecting, replies, scoring, quotes, or CRM cleanup. We'll send back an honest read on what to automate first, and what production would actually look like.
The AI Operations Audit maps your workflows, finds the automations that return within 90 days, and hands you a prioritized build plan you own — whether or not we build it.