Overstand Labs

What do they actually do

Overstand Labs pulls a company’s customer conversations (Slack, email, WhatsApp, call transcripts, tickets, meeting notes) into one place, analyzes them for actionable signals (feature requests, bugs, churn risk, upsell cues), and surfaces those signals via a leader-facing dashboard and an API. Each insight links back to the original messages so executives and product leaders can see the evidence before acting. Website · YC profile

Teams connect existing channels without changing workflows. Overstand continuously ingests conversations, flags patterns, and delivers alerts or an overview dashboard; integrations and the API let teams push structured signals into CRM or ticketing systems. The company is early-stage (YC Winter 2025) with a small team and a pre-seed raise, and it sells through demos/pilots today. Website · YC profile · Crunchbase

Who are their target customer(s)

• Founder / CEO (enterprise or scale-up): Relies on second-hand summaries and meeting notes instead of direct customer signals, making it easy to miss fast-moving issues or revenue opportunities and hard to decide where to spend personal time. YC profile · Website
• Head of Product / Product leader: Feedback and requests are scattered across Slack, tickets, calls, and email, which slows prioritization and makes it hard to justify tradeoffs. Overstand consolidates and ties trend signals back to source messages. Website
• CRO / Sales leader: Upsell and cross-sell cues in support and account conversations often go unnoticed, so teams miss warm revenue signals. Overstand previously emphasized detecting cross-sell opportunities in customer interactions. YC profile
• Head of Customer Success: Churn indicators are buried across channels and show up late, forcing reactive firefighting. Overstand aims to surface early churn and risk signals from unified conversation data. Website
• Support / Operations manager: High volume and multiple channels make it hard to spot systemic bugs or recurring issues, leading to time spent on manual reporting instead of root-cause fixes. Overstand links insights back to messages to reduce manual triage. Website

How would they acquire their first 10, 50, and 100 customers

• First 10: Leverage YC and founder networks to run tightly scoped, hands-on pilots tied to a single exec KPI; ship integrations quickly, do daily check-ins, and produce short case studies with permissioned quotes and demo clips. YC profile · Website
• First 50: Turn the pilot playbook into a repeatable outbound motion in a few target verticals; add 1–2 reps for account-based outreach and close similar scale-up accounts using standardized pilot contracts, connector templates, and a one-page success plan. Website
• First 100: Scale channels: publish playbooks/SEO content, list in partner marketplaces, and offer a lower-friction paid pilot or self-serve tier. Add security/compliance collateral, formalize customer success, and use early customers as references to accelerate larger deals. Website

What is the rough total addressable market

Top-down context:

Overstand sits at the intersection of CRM, conversational AI, and AI in customer experience. Those adjacent markets total in the tens of billions today; a conservative overlapping slice for leadership-focused conversation insights is roughly $20–40B globally. Statista · Grand View Research · The Business Research Company

Bottom-up calculation:

Targeting mid-market and enterprise firms in the U.S. and EU (hundreds of thousands in total; tens of thousands relevant) with ACVs in the $25k–$100k range implies a reachable market from hundreds of millions to low billions. Example scenarios: 1,000 customers × $50k = $50M; 10,000 × $25k = $250M. Eurostat · U.S. Census SUSB · SaaS Capital · SaaStr

Assumptions:

• Do not sum adjacent markets; TAM is the overlapping slice of CRM/CX/conversational AI budgets that fund analytics/insights.
• Initial ICP is mid-market and enterprise software-centric firms, not the full firm counts in U.S./EU.
• ACVs land in the $25k–$100k range depending on depth of integrations and buyer segment.

Who are some of their notable competitors

• Gong: Conversation intelligence for revenue teams: captures calls/meetings/emails and surfaces deal risks, buying signals, and coaching insights. Overlaps on turning customer voice into leader alerts but is sales-focused. Source
• Chorus (ZoomInfo): Sales call analytics and deal intelligence focused on meetings and email threads to improve forecasting and coaching; overlaps on conversation-derived signals for GTM teams. Source
• Observe.ai: Contact-center analytics and automation that analyzes 100% of interactions for QA and agent workflows; overlaps on trends/risk from spoken interactions but built for high-volume contact centers. Source
• Medallia: Enterprise experience management/Voice-of-Customer platform collecting survey, voice, chat, and social signals with analytics and action workflows; broader, implementation-heavy alternative to an API/dashboard-led approach. Source
• Productboard: Product feedback centralization and prioritization from tickets, Slack, and calls; overlaps on surfacing feature requests but optimized for turning feedback into product workstreams. Source