vaibhav
aher. Resume, one page
GTM systems engineer · currently at Otera

Outbound,
engineered.

I build the machine that books the meetings: domains, data, signals, and the agents that run them. Then I hand it to your team and it keeps running.

See the campaigns
CURRENTLYGTM Engineer, Otera BASED INMumbai, working globally OPEN TOGTM engineering roles
Vaibhav Aher
EXHIBIT ABuilds the machine.
Hands over the keys.

01 / Who I am

Solving revenue problems,
one agentic loop at a time.

I'm a GTM engineer. I believe revenue problems are systems problems.
So I build agentic systems, one loop at a time.

A loop is not a dashboard or a deck. Something watches for a signal, qualifies the account, writes the message, sends it, reads the reply, and feeds what it learned back to the start. I build that from zero, domains, data, agents and the code underneath, then hand it to the team and it keeps running. Every number on this page is a live pull from the platform that sent the email, or a screenshot of it.

Start from the revenue problem.Build the loop, not the deck.Kill on the data.

02 / Where I've shipped

Production code,
tied to revenue.

Three roles, four fractional clients.
Read left to right, newest first.

03 / The campaigns

Real plays.
Real numbers.

Performance and method only.
The copy stays with the clients who paid for it.

● ● ●all campaigns / five clients / 2026replies, not opens
#ClientWho, whatCellsSentLeadsRepliesReply ratePositiveWhenSource
01Skydive skydive.com ↗B2B startups, 15–50 people · AI teammates2015,0298,2043984.85%35 interested, floorJun – Sep 2026Smartlead API
02Pemo pemo.io ↗UAE SMBs · corporate cards611,6186,1251221.99%53 interestedJul – Sep 2026Smartlead API
03Visbl visbl.com ↗Licensed brokers, US · vertical FinTech marketplace13,2033,203531.65%22 interested · 41.5% of repliesJan 2026Dashboard
04getdot.ai getdot.ai ↗RevOps, data and analytics leaders · AI analyst519,67711,857940.80%32 positive · 34.0% of repliesJan – May 2026Dashboard
05BuildWithWave buildwithwave.com ↗Restoration companies, US · vertical AI SaaS25,2965,296581.76%9 opportunities · $4,500Mar – May 2026Dashboard
Blended5 clients · 34 campaign cells3454,82334,6857252.09%1512026
Reply rate = replies ÷ leads contacted, as the sending platform reports it (BuildWithWave: Instantly’s basis; raw 58 on 5,296)Skydive + Pemo pulled live from the Smartlead API · others from the dashboard screenshots shown on each card

04 / Three more

The list is
the message.

Where the list came from mattered more than what it said.
Click any window to enlarge the platform readout.

Platform readout · Jan to May 2026 ● ● ●getdot.ai / all campaigns↗getdot.ai campaign dashboard: 19,677 sent, 94 replies, 32 positive 34% positive reply rate
03Cold outbound / AI analytics SaaSgetdot.ai ↗

getdot.ai.

Five angle families ran as separate cells against the same audience of data and analytics leaders: stack detection, recurring exec reporting, business-review prep, a single diagnostic question, the internal request queue. Positive-reply rate was the only verdict. 19,677 sent, 94 replies, 32 positive: 34%. Copy withheld, client work.

Platform readout · registry-sourced list ● ● ●mortgage brokers / NMLS↗FinTech campaign dashboard: 3,203 sent, 53 replies, 22 interested 41.5% positive reply rate
04Cold outbound / vertical FinTech marketplace / mortgage brokersvisbl.com ↗

Visbl.

Pulled the list straight from the NMLS, the federal registry for the mortgage industry, then enriched and qualified it in Clay on company size, office footprint and active licences. 3,203 sent, 53 replies, 22 interested. Bounces ran high because registry data is not database data, even after a three-step validation pass. Worth it for a list nobody else had.

Platform readout · two signal plays ● ● ●buildwithwave / restoration↗BuildWithWave campaign dashboard: 5,296 sequences, 58 replies, 9 opportunities 9 opportunities · $4,500
05Cold outbound / vertical AI SaaS / restorationbuildwithwave.com ↗

BuildWithWave.

Two plays for restoration companies. A negative-review detector in Clay and Apify that reads every public review and surfaces the customer complaint this product solves, so the complaint becomes the reason for the email. And a custom Python scraper of the IICRC certification registry, which no enrichment tool sells, to reach only the operators professional enough to have bothered. 5,296 sequences, 58 replies, 9 opportunities. Both plays swap "who fits the firmographics" for "who has shown the problem in public". The second question has far fewer people in the answer.

Watch the automation walkthrough

Who replied

Replies came in
from teams at.

Pooled across all five clients on purpose: no company here is attributable to a client.
490+ companies replied in total; this is a selection.

Sendososendoso.comAffinityaffinity.coHippocratic AIhippocraticai.comConductorconductor.comClaravineclaravine.comAxios HQaxioshq.comClayclay.comProvisprovis.aeBlack Forest Labsblackforestlabs.aiVast.aivast.aiCoefficientcoefficient.ioLabsterlabster.comTimelefttimeleft.comPolyAIpoly-ai.comTamrtamr.comShapoorji Pallonji Propertiesshapoorjiproperties.aeAlfardanalfardan-corporation.comStravastrava.comMaven Clinicmavenclinic.comOMRomr.combeehiivbeehiiv.comFingerprintfingerprint.comDynamic Propertiesdynamicproperties.aeHG Insightshginsights.comAtScaleatscale.comWasabiwasabi.comFunction Healthfunctionhealth.comSendososendoso.comAffinityaffinity.coHippocratic AIhippocraticai.comConductorconductor.comClaravineclaravine.comAxios HQaxioshq.comClayclay.comProvisprovis.aeBlack Forest Labsblackforestlabs.aiVast.aivast.aiCoefficientcoefficient.ioLabsterlabster.comTimelefttimeleft.comPolyAIpoly-ai.comTamrtamr.comShapoorji Pallonji Propertiesshapoorjiproperties.aeAlfardanalfardan-corporation.comStravastrava.comMaven Clinicmavenclinic.comOMRomr.combeehiivbeehiiv.comFingerprintfingerprint.comDynamic Propertiesdynamicproperties.aeHG Insightshginsights.comAtScaleatscale.comWasabiwasabi.comFunction Healthfunctionhealth.com
Replitrepl.itCodeSignalcodesignal.comDigitsdigits.comAllTrailsalltrails.comTradelingtradeling.comDescriptdescript.comLumoslumos.comPlanhatplanhat.comSpotHerospothero.comObserve.aiobserve.aiAirOpsairops.comHarmonicharmonic.aiBoopinboopin.comAllsopp & Allsoppallsoppandallsopp.comPayrailspayrails.comGoldmarkgoldmark.aeOpenWebopenweb.comBridgebridge.xyzGuardzguardz.comReplicantreplicant.aiNuwa Capitalnuwacapital.ioSauce Labssaucelabs.comLocation Solutionslocationsolutions.comAgoraagora.aeTwelve Labstwelvelabs.ioMintlifymintlify.comParityparity.ioReplitrepl.itCodeSignalcodesignal.comDigitsdigits.comAllTrailsalltrails.comTradelingtradeling.comDescriptdescript.comLumoslumos.comPlanhatplanhat.comSpotHerospothero.comObserve.aiobserve.aiAirOpsairops.comHarmonicharmonic.aiBoopinboopin.comAllsopp & Allsoppallsoppandallsopp.comPayrailspayrails.comGoldmarkgoldmark.aeOpenWebopenweb.comBridgebridge.xyzGuardzguardz.comReplicantreplicant.aiNuwa Capitalnuwacapital.ioSauce Labssaucelabs.comLocation Solutionslocationsolutions.comAgoraagora.aeTwelve Labstwelvelabs.ioMintlifymintlify.comParityparity.io

Names and domains from the sending platforms’ reply logs, 17 Sep 2026. No logos, no client mapping, no reply text.

What ties it together

The list is the message.
The audience is the copy.
The data is the boss.

Every figure on this page is a live pull from the sending platform, a hand-classified reply export, or a screenshot of the dashboard. Nothing is inflated, and the one estimate (25+ meetings a month) is the client's own count.

05 / The systems

Things I built
that run without me.

Two Claude Code apps, one list engine,
two n8n pipelines. All in production.

houseofgrowth.vercel.app / dashboard / outset.ai
AI citations84%
Mentions41
Share of voice12%
ChatGPT · Claude · Perplexity · Gemini ↗
01Claude Code build / GEO, AI search

AI Visibility Dashboard.

For Houses of Growth. Enter any domain and get a full AI visibility report: how often the brand is cited by ChatGPT, Claude, Perplexity and Gemini, share of voice against competitors, and concrete GEO recommendations. Next.js, Supabase, OpenAI, Apify; the query fan-out parallelised with BullMQ and Redis.

Live report: outset.ai GitHub
Universe list engine · recall first, precision second
  1. 01
    Recall sweepProspeo · 16 countries · every plausible firm in the sector
  2. 02
    Ground-truth promptLabelled set first · 25/25 on the hold-out before touching the universe
  3. 03
    Relevance passOpenAI Batch API + web search · in-sector only
  4. 04
    Ledgered loadSource, rows, verification, suppression screen, logged before launch
02Claude Code build / list intelligence

Universe List Engine.

Sector-complete prospect universes for Houses of Growth's finance push: investment banking and M&A advisory across the US, Canada and 15 European countries, then private equity. Sweep everything that could be in-sector, then let a ground-truth-calibrated LLM pass decide what stays. Off-the-shelf databases give you whoever paid to be listed. This gives you the sector.

Brand OS · a brand kit agents can read
Brand voicetone docs
ICP builderideal customers
Positioningmessaging framework
GTM playbooklaunch strategy
Claude API · Next.js · one input, one kit ↗
03Claude Code build / brand intelligence

Brand OS.

Built for Qove.ai. Input a company and get a complete brand kit: voice guidelines, ICP definitions, positioning framework, messaging hierarchy and GTM playbook, structured so content and outreach agents can build on it and stay on-brand without a human checking every output.

Live demo GitHub
n8n · slack → research → claude → drive → sequencer ● ● ●lead-magnet-generator.json↗n8n workflow canvas for the lead magnet generator
04n8n build / AI automation

Lead magnet generator.

Drop a company domain in Slack. The workflow finds decision makers, maps the competitor landscape, scrapes the company's own site, then has Claude write a lead magnet report specific to that company. Saved to Drive, team pinged, contact pushed into the sequencer. Research to send with zero manual steps.

Read a sample output
n8n · competitor ad audit → live programmatic SEO post ● ● ●trymesha.com / blog / ad-audits↗Published ad audit page on the client domain
05n8n build / martech / shipped in under a month

Ad audit to programmatic SEO.

Triggered from Slack, the workflow audits a competitor's Facebook ads and landing pages for message alignment and technical performance, then publishes the findings as a live programmatic SEO post on the client's domain. o3 for the reasoning pass, Claude for the human-grade write-up, Apify and Firecrawl covering about 90% of target web assets, and a decision tree that separates high-priority findings from noise before anyone gets alerted. Internal research becomes a public marketing asset with no human in the loop.

View a live output Workflow canvas ↗

06 / The toolkit

What it's
built with.

Production code, not configuration.
Python, TypeScript, SQL, and the GTM stack around them.

07 / Next

Let's build something
that runs itself.

Open to GTM engineering roles and fractional engagements. I ship the infrastructure, the data, the signals and the agents, then hand your team a system it can run. Based in Mumbai, working globally.

01vaibhavva219@gmail.com 02linkedin.com/in/vaibhavvaher 03github.com/VaibhavAher219 04x.com/vaibhavvaa Resume, one page (PDF)

Replies within a day, India hours. No agency, no subcontracting.