Taito.ai runs its whole pipeline on data nobody types in

The AI-native people operations platform brought product usage, invoicing, and meeting notes into the same place as its deals. Records update themselves, handovers no longer need meetings, and the team spends 50% less time maintaining pipeline data.

Zero is more like our go-to-market brain. It sees what happens with a customer across the product, meetings and billing, and keeps the pipeline up to date on its own.

Miikka Kataja
Miikka KatajaGTM at Taito.ai

Challenge

Pipeline reviews nobody wanted to run

Miikka Kataja was Taito.ai's first go-to-market hire. He owns top-of-funnel, qualification, and the GTM tooling, and closed the company's first deals without founder involvement. Taito's model is high-velocity by design: reach SMB and mid-market people & HR teams, get them into a free trial, and get them to value fast.

The tooling didn't keep up. The team used Attio, with Clay for account and contact data and Lemlist for sequencing. Attio stayed underused because keeping it current required manual data entry, and the workflows Miikka wanted to build needed engineering work he didn't have access to.

The data the team actually cared about lived somewhere else entirely. Product usage sat in PostHog, invoicing in Stripe, meeting notes in Fireflies. Checking a customer's health meant opening PostHog and filtering manually. Handovers from sales to trial started with the same questions every time: what's the status of this deal, what was discussed?

The result was stale records and pipeline reviews nobody wanted to run. Nobody trusted the data on the screen. For a company whose whole product thesis is that software should do the busywork, the go-to-market stack involved a surprising amount of manual work.

Pipeline reviews felt like a chore because the data was outdated and nobody trusted it. People stopped wanting to run them.

Miikka Kataja
Miikka KatajaGTM at Taito.ai

Solution

Every deal updates itself from product, billing and meetings

The migration was fast. Taito connected the systems its team already used to Zero, so the data that used to live outside the sales process could start updating deals automatically.

PostHog, Stripe, and Fireflies now feed Zero automatically. Each deal shows product activity, invoice status, and the latest meeting notes in one place instead of burying that context across three separate tools.

AI columns keep records up to date without manual entry. A customer's tech stack updates from the latest discussion or email thread. Taito uses SPICED for sales qualification, and every deal has a card that summarizes calls and emails against that framework. Handovers stopped being meetings because the context is already on the record.

Friday pipeline and customer reviews are running again because the team trusts what it sees. Discovery notes, invoicing, and product activity are already on each record. Nobody has to spend the week updating the system just so the review can happen.

The rest of the team builds on it too. Taito's customer lead runs a customer health dashboard in Zero. The product lead is testing trial activation emails, drafted automatically by Zero's sequences and workflows when someone starts a trial. And the team uses Zero's Slack bot daily, syncing Slack threads to deal notes in Zero.

One of Taito's team values is "automate all manual work." Go-to-market finally complies.

We use the Slack bot every day. We can add Zero to a discussion, save the context to the customer record, pull up the last meeting, or prep for the next one.

Miikka Kataja
Miikka KatajaGTM at Taito.ai

Results

50% less admin as the pipeline grows

Taito started building the pipeline for its new product around the same time it adopted Zero. Since then, hundreds of marketing-qualified leads and dozens of paying customers have been sourced, tracked, and closed in Zero.

Miikka estimates the team now spends at least 50% less time on pipeline and data maintenance than before. AI columns and integrations handle the copy-pasting, field updates, and status-chasing. As volume grows, the goal is to let Zero absorb more of that operational work instead of adding it back to the team.

Our engineering team is doing amazing things with AI. With Zero, our go-to-market team can now operate the same way.

Miikka Kataja
Miikka KatajaGTM at Taito.ai

Write the next
story with us

Start for free