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Later Tech Stack

Influencer marketing platform with creator intelligence and campaign management

Marketing Services Boston, Massachusetts 201–500 employees Founded 2014 Privately Held
later.com LinkedIn

Later operates an influencer marketing platform for brands and agencies, built on creator data and campaign analytics. The tech stack spans React, TypeScript, Node.js, and PostgreSQL on AWS, with BigQuery and Kafka handling analytics and event streaming—a mature, data-driven architecture. Active hiring is concentrated in sales (17 roles) and marketing (14 roles), with security and infrastructure work visible in projects around CI/CD hardening and application decomposition, suggesting a transition toward enterprise-grade operations and stricter compliance posture.

Tech Stack 34 technologies

Core StackTableau Looker Power BI React TypeScript Node.js C# PostgreSQL Docker Kubernetes AWS HubSpot Salesforce Figma Flask CloudWatch Prometheus Grafana BigQuery Ruby on Rails React Native Kafka Django Laravel X Pinterest Snapchat Segment Domo GCP+1 more
AdoptingAdaptive Planning Planful Anaplan

What Later Is Building

◆Challenges

  • Fear and guesswork in influencer marketing
  • Scaling customer operations
  • Identifying monetization opportunities
  • Technical debt reduction
  • Net revenue retention
  • Enterprise partnership acquisition
  • Strengthening security foundations
  • Bridging sales and services
  • Ensuring efficient revenue conversion
  • Scalability challenges

▲Active Projects

  • Acquire new mid-market and enterprise accounts
  • Grow wallet share within existing clients
  • Pipeline-to-capacity forecasting models
  • Scalable sales processes
  • Strategic business reviews
  • Building internal security tooling
  • Embedding security into ci/cd pipelines
  • Monolithic application decomposition
  • Integration strategy for heterogeneous systems
  • Secure authentication systems

Hiring Activity

Accelerating60 roles · 25 in 30d

Department

Sales
17
Marketing
14
Engineering
7
Ops
5
Security
4
Support
3
Finance
2
HR
2

Seniority

Senior
28
Mid
10
Manager
7
Director
4
VP
3
Junior
2
Intern
1
Lead
1

Notable leadership hires: Director of Partnerships

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About Later

Later is an influencer marketing and creator partnership platform headquartered in Boston. The product helps brands identify and collaborate with creators, backed by intelligence tools that reduce guesswork in campaign selection and execution. The company serves mid-market and enterprise brands, with current growth initiatives focused on expanding into new customer segments and deepening wallet share within existing accounts. Recent projects reveal internal scaling challenges—monolithic application decomposition, security tooling, and revenue forecasting models—alongside external push toward enterprise partnerships and customer success infrastructure.

HeadquartersBoston, Massachusetts
Company Size201–500 employees
Founded2014
Hiring MarketsUnited States, Canada

Frequently Asked Questions

What tech stack does Later use?

Later runs React, TypeScript, and Node.js on the front end; PostgreSQL and BigQuery for data; Kafka for streaming; Docker and Kubernetes for deployment on AWS. Analytics tools include Tableau, Looker, and Power BI. CRM and marketing automation layer Salesforce and HubSpot.

What is Later working on?

Later is scaling sales and customer operations toward mid-market and enterprise (pipeline forecasting, scalable processes, strategic reviews). Engineering priorities include monolithic decomposition, heterogeneous system integration, CI/CD security embedding, and authentication systems—indicating a move from startup infrastructure toward platform maturity.

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How this profile is built

Later's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.