Engineering partner for startups

Build your product.
Move it forward.

BINEARY helps startups turn ideas into working software — from a first MVP to the product you already run. We work with you on scope, technology, development, and deployment, with clear milestones and direct communication.

Discuss your projectExplore our services

Starting from an idea? We scope an MVP around the smallest release you can put in front of real users, then build and deploy it.

Start with an MVP

Curiosity, Engineered. Founder-led product, backend, data and cloud engineering.

Services

What we can build and improve with you.

From a first release to a product that’s already running, the work is scoped around what your product needs next.

01

MVP & product development

Scope and build MVPs, web applications, dashboards, and internal tools around a clear first release.

Typical deliverables

  • MVP scope: the smallest release worth shipping
  • Web app, dashboard or internal tool
  • Backend services and data model
  • Deployed, documented first release
02

Existing product engineering

Extend features, connect systems, investigate performance issues, and improve maintainability in an existing codebase.

Typical deliverables

  • New features built into your codebase
  • Performance investigation with written findings
  • Fixes for the bottlenecks that matter
  • Refactoring and tests where they reduce risk
03

APIs, integrations & data

Build APIs, service integrations, automated workflows, and pipelines that connect a product’s data and operations.

Typical deliverables

  • APIs with documentation
  • Third-party and internal service integrations
  • Scheduled and event-driven workflows
  • ETL/ELT pipelines and data models
04

Cloud & delivery

Set up deployment environments, CI/CD, monitoring, and infrastructure appropriate to the project.

Typical deliverables

  • Staging and production environments
  • CI/CD pipelines from commit to deploy
  • Logging, monitoring and alerts
  • Infrastructure as code where it fits

Principle

Technology follows the product.

Stack decisions start from your existing codebase, your requirements, your budget, and who will maintain the system later — not from a preferred toolkit. Where a project needs a technology outside our experience, we say so up front and plan for it.

Starting strengths: Python · Backend engineering · Data systems · Cloud infrastructure.

Experience

Selected engineering experience

These examples come from the founder’s prior engineering work in backend, cloud and data systems. They show the kind of problems BINEARY is set up to take on — they are not presented as BINEARY client case studies.

01

Notifications microservice

A standalone service that owns how a platform’s messages are delivered.
Problem
Messaging logic was easy to duplicate across products, which made delivery, retries and edge cases harder to own.
Founder’s contribution
Designed and implemented the service boundary, the event flow and the delivery responsibilities, so products emit events and the service owns the message lifecycle.
Outcome
One clear owner for delivery and a reusable path that products can call instead of re-implementing messaging.
Technologies
MicroservicesEvent-driven designDelivery workersRetries
How it works:
  1. 01Product emits an event
  2. 02Notifications service routes it
  3. 03Delivery workers send it
  4. 04Failures are retried
02

Cloud environments and CI/CD

AWS and Azure environments, with pipelines from commit to deployment.
Problem
Infrastructure built through manual console steps, and releases that depend on someone’s local sequence, are hard to review, reproduce and hand over.
Founder’s contribution
Set up environments on AWS and Azure end to end, from networking to running workloads, and built CI/CD pipelines with GitHub Actions and AWS-native tooling.
Outcome
Environments that can be rebuilt deliberately, and releases that follow a visible build → test → deploy path.
Technologies
AWSAzureGitHub ActionsAWS-native CI/CD
How it works:
  1. 01Commit
  2. 02Build
  3. 03Test
  4. 04Deploy to the cloud environment
03

Scheduled API workflows with Airflow

Time-based integrations with dependencies, retries and run history.
Problem
Scheduled API calls need more than a cron expression: failures have to be visible and recoverable.
Founder’s contribution
Built Apache Airflow DAGs to schedule the API calls, express task dependencies, retry failed tasks and keep run state inspectable.
Outcome
Each run can be checked at a glance: what succeeded, what retried, and what needs attention.
Technologies
Apache AirflowDAGsAPI integrationsRetries
How it works:
  1. 01Schedule triggers a run
  2. 02Dependent tasks call APIs
  3. 03Failed tasks retry
  4. 04Run state is recorded
04

ETL/ELT pipelines on a medallion model

Prefect workflows that move data through bronze, silver and gold layers.
Problem
Large data workflows need clear stages so raw inputs, cleaned records and modelled data don’t collapse into one opaque job.
Founder’s contribution
Built Prefect ETL/ELT workflows around a bronze → silver → gold medallion architecture, with orchestration across each stage.
Outcome
A staged pipeline in which each layer has a defined purpose. In this prior work, the pipelines processed more than 40 million rows.
Technologies
PrefectETL/ELTMedallion architecturePython
How it works:
  1. 01Source data lands in bronze
  2. 02Cleaned into silver
  3. 03Modelled into gold
  4. 04Orchestrated by Prefect
05

API performance work

Profiling slow endpoints to find and fix the real bottleneck.
Problem
Slow API paths often hide the underlying cause behind symptoms, such as an expensive query or repeated work in the request path.
Founder’s contribution
Profiled the request path, isolated the bottleneck, optimised the work on the hot path and measured again.
Outcome
Response times on the optimised paths came down to milliseconds, with the cause fixed rather than masked.
Technologies
API profilingQuery optimisationPerformance measurement
How it works:
  1. 01Profile the request
  2. 02Isolate the bottleneck
  3. 03Optimise the hot path
  4. 04Measure again

Working on something similar? Discuss your project.

How we work

Four stages, from first conversation to handover.

Every engagement follows the same shape, so you know what happens next and what you’ll have at the end of each stage.

  1. 01

    Understand

    Discuss the product, its users, the current system, constraints, and the outcome you need.

  2. 02

    Scope

    Agree on deliverables, technical approach, milestones, responsibilities, and acceptance criteria.

  3. 03

    Build

    Implement in reviewable increments, share progress, and demonstrate completed work.

  4. 04

    Launch & continue

    Test, deploy, document, and hand over. Ongoing maintenance or further development is agreed separately.

Founder-led

You talk directly to the engineer leading the work.

BINEARY is founder-led, so the person you explain the problem to is the person scoping and building the solution. Questions, trade-offs and progress updates don’t pass through an account manager.

Engagement options

Three ways to work together.

Pick the shape that fits where your product is. The details — scope, capacity and milestones — are agreed in the project discussion.

Scoped project

A defined deliverable with agreed milestones and acceptance criteria.

Good for an MVP, a new feature or a specific integration.

Ongoing engineering

A prioritised backlog with agreed capacity and regular review cycles.

Good for a product that needs continued development.

Technical discovery

A review of your idea or existing system that ends in an implementation plan.

Good when you need clarity before committing to a build.

Discuss your project

Not sure which fits? Describe the problem and we’ll suggest one.

Contact

Tell us what you’re building.

Share your idea, your current product, or the engineering problem you need help with. Include your priorities and any timeline or budget constraints.

What do you need?

Sent to gaurav@bineary.com. Used only to reply to you.