Real results. Real teams.

PostHog

Developer Tools

PostHog ships in public and gets feedback from GitHub, Zendesk, Slack, email, social, sales, and product conversations. Engineers and PMs needed customer context where they already work — especially GitHub issues. BuildBetter can help by collecting qualitative feedback, keeping source context attached, and linking relevant customer detail back to the issues engineers and PMs already track.

Brex

Financial Operations

Brex had customer feedback coming from sales calls, Slack submissions, CRM data, Snowflake context, and manual reporting workflows. The problem was not a lack of feedback. The problem was making that feedback clean, attributable, and usable across product, CX, GTM, and marketing workflows. BuildBetter helped Brex connect feedback to customers and companies, extract useful clusters from messy data, answer questions with AI chat, and move signals toward workflows like Slack updates, reports, and product follow-up.

Orah

Education Technology

Orah had feedback coming from Salesforce, Intercom, Slack, Gong, Google Meet, custom forms, and internal product workflows. The problem was not that Orah needed another place to collect feedback. The problem was that product analysis still required manually assembling customer, company, revenue, integration, support, and call context. BuildBetter gave Orah the analysis layer: multi-source ingestion, signal extraction, clustering, documents, API access, MCP direction, and a way to connect feedback to customer and company context.

MNTN

Connected TV

MNTN had conversations happening across PMO, engineering, product marketing, revenue, customer success, IT, people operations, and leadership. The product created real internal interest. Teams saw uses for meeting summaries, searchable context, PMO workflows, CS reporting, manager visibility, Gong enrichment, and even People Ops recordings. The blocker was not product interest. The blocker was scale: permissions, privacy, recording access, admin controls, ownership, tool duplication, and IPO-driven consolidation.

Sonder

Employee Wellbeing

Sonder uses BuildBetter to capture meeting notes, decisions, and customer context so teams can follow the thread of a conversation after the meeting ends.

Springboard

Education

Springboard had important conversations happening across company meetings, product and engineering calls, coaching sessions, student-facing workflows, and internal operations. BuildBetter helps the team summarize, extract signal, generate custom documents, and use AI chat while respecting privacy, consent, and workspace boundaries.

Gorgias

Customer Support

Gorgias had customer feedback coming from support tickets, sales calls, customer interviews, Slack, product-feedback workflows, and CRM context. The problem was not a lack of customer data. The problem was turning scattered feedback into product signal that product, research, GTM, and customer-facing teams could actually use. BuildBetter gave Gorgias one place to centralize feedback, extract structured signals, organize them by product area and customer context, and reuse them across research, product, leadership reporting, and GTM prep.

Cytracom

Unified Communications

Cytracom runs five products for MSPs — and the customer signal behind them lived in Gong, Zoom, Fathom, Krisp, Zendesk, HubSpot, PostHog, and Atlassian. Each tool held a slice. None of them connected what customers said to what the company shipped. BuildBetter became the layer underneath: every call, ticket, and product event across all five products, in one place, feeding product, customer success, and go-to-market.

AppFolio

Property Management

AppFolio’s Product Ops team uses BuildBetter as a searchable place for research conversations, summaries, highlights, and shareable takeaways. Product Ops needed research to reach more stakeholders without turning every insight into a one-off handoff. BuildBetter gives the team a repeatable way to move from raw conversations to summaries, highlights, links, and shareable context.

Drip

Marketing Automation

Drip had demos, sales calls, customer success calls, product conversations, and CRM context. The problem was not a lack of recordings. The problem was that sales kept hearing the same objections and integration requests, but product needed evidence. BuildBetter turned demo conversations into data the GTM, product, and leadership teams could act on.

WellSpoken

Healthcare Operations

WellSpoken uses BuildBetter to review staffing calls, compare candidates against strong hires, and help managers coach support calls without spending the week in recordings.

Andros

Healthcare Technology

Andros had valuable customer and prospect conversations happening in Chorus, plus feedback spread across Salesforce, Zendesk, Jira, and spreadsheets. The problem was not a lack of customer feedback. The problem was that the richest feedback lived inside a sales tool that was not built for product research, while the rest of the feedback was scattered across tools and documents. BuildBetter gave Andros a way to evaluate a better path: pull product signal from sales conversations, consolidate unstructured feedback, generate source-backed documents, and analyze customer conversations with PHI-aware workflows.

Trolley

Enterprise Software

Trolley had customer data across Salesforce, Momentum calls, Slack customer channels, support cases, product taxonomy, and product planning workflows. The problem was not a lack of customer data. The problem was turning that data into a structured, trusted signal layer product, PMM, content, executives, and workflows could actually use. BuildBetter helped Trolley connect customer conversations and company metadata, apply product taxonomy, enrich feedback with account and revenue context, and make customer signal usable across product, PMM, content, executive reporting, and workflow automation.

Easy As Pie

Healthcare Consulting

Easy As Pie needed a recording and insight partner they could recommend to healthcare clients. BuildBetter met the compliance bar, supported onboarding for new team members, and gave Danielle a partner for future AI services work.