Developer Tools • Founding Engineer

Dromo scaled from 0→1 to production-grade data import platform

HyperNest embedded a founding engineer to build core platform features, scale infrastructure, and support Dromo's growth from MVP to enterprise-ready product.

0→1

Build phase

CSV, XLS, TSV

File types

SOC 2 Type II

Compliance

Scaling

Status

Add a founding engineer

Client snapshot

Company
Dromo
Industry
Developer Tools / Data Infrastructure
Stage
Seed → Growth
Headquarters
San Francisco, CA
Website
dromo.io/

Timeline

  1. Phase 1

    Built core importer MVP with validation engine and AI column matching.

  2. Phase 2

    Implemented SOC 2 compliance, HIPAA readiness, and GDPR privacy controls.

  3. Phase 3

    Scaled platform to handle enterprise workloads with headless API and self-hosted options.

  4. Ongoing

    Continue to ship features, maintain reliability, and support growth.

Problem → Action → Outcome

A quick operator-level summary of what changed.

Problem

A developer tools startup needed to build an enterprise-grade data import platform from scratch, requiring AI features, multi-format support, and compliance certifications.

Action

HyperNest embedded a founding engineer who owned the full stack—building AI column matching, compliance infrastructure, and scalable architecture.

Outcome

Dromo shipped a production platform with SOC 2 Type II certification, 4.9/5 star ratings, and customers like Upkeep.com reporting 98% reduction in onboarding errors.

The challenge

Dromo needed to build a best-in-class data import solution that could compete with established players. They required engineers who could own the entire stack—from AI-powered column matching to enterprise compliance—while moving fast enough to capture market opportunity.

  • –Building AI-powered features (GPT column matching, data editing) from scratch
  • –Achieving SOC 2 Type II, HIPAA, and GDPR compliance for enterprise sales
  • –Supporting multiple deployment modes: embedded, headless API, and self-hosted
  • –Handling messy real-world data at scale without compromising reliability

What we built

HyperNest embedded a founding engineer who joined as a core team member. Thari Zef shipped features across the full stack while maintaining the velocity and ownership expected of a first employee.

Built AI-powered column matching and data transformation features
Implemented privacy-first architecture with browser-only processing mode
Developed headless API with SFTP support for enterprise integrations
Created validation engine supporting CSV, XLS, XLSX, and TSV formats
Established compliance infrastructure for SOC 2, HIPAA, and GDPR

Impact

Dromo now serves companies like Upkeep.com and has earned recognition as a High Performer on G2. The platform handles enterprise-scale data imports with 98% reduction in onboarding errors for customers.

Shipped production-grade platform from initial concept to enterprise-ready
Achieved SOC 2 Type II certification and HIPAA compliance
Built features that earned 4.9/5 stars on G2 and 5/5 on other platforms
Enabled seamless integrations with Google Drive, OneDrive, Slack, and 100+ services

Stack & capabilities

Tools, platforms, and competencies we owned for this engagement.

Frontend

  • React
  • TypeScript
  • Tailwind

Backend

  • Node.js
  • Python
  • PostgreSQL

AI & Data

  • OpenAI GPT
  • Custom ML Models
  • Data Validation Engine

“HyperNest helped us build Dromo from zero to one and continues to be a critical partner as we scale. Their founding engineer embedded with our team like a full-time hire—shipping features, owning reliability, and never needing to be managed.”

Albert Aznavour

Chief of Staff, Dromo

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How this applies to other startups

  • •Developer tools companies can use the same embedded engineer model to ship complex features without the overhead of a large team.
  • •Startups needing SOC 2 or HIPAA compliance can reuse the compliance-first architecture patterns we built at Dromo.
  • •Teams building AI-powered features can apply the same iterative approach to shipping GPT integrations into production.