We build apps that save every change on the device first, sync it in the background and show live updates across devices. Users keep working when the signal drops, and clear conflict rules stop one person's changes overwriting another's.
What's included
6 capabilities, delivered by one squad. Use what you need now and add more as you grow.
Durable local writes and indexed reads keep the app fast, even with no connection.
Changes queue on the device and sync with retries. Each operation can safely run twice without creating a duplicate.
Clear rules for merging changes made in two places, so devices don't overwrite each other or quietly drift apart.
WebSockets, subscriptions and event streams that keep teams in sync as things happen.
Batched writes and polling that adapts to the connection, so the app copes with weak mobile networks.
Tracing, audit logs, failure reasons and alerts that keep data correct as usage grows.
Our approach
The usual way
Every save needs a round trip to the server, so users lose work when the signal drops.
How we do it
Every action is saved locally first, then synced in the background with retry and replay.
The usual way
Duplicate updates, overwrites and silent differences between devices.
How we do it
Repeat-safe operations, versioning and merge rules keep data consistent across devices.
The usual way
When data looks wrong, there are no traces or logs to show what happened.
How we do it
Every sync is traced with failure reasons, and operations can be replayed in sequence to show what happened and why.
Architecture
Each layer has a clear job, so the system is easier to secure, test and extend.
Transactions, indexing and offline reads and writes that make the app feel instant.
Queued operations with retries and batching, safe to repeat without creating duplicates.
Push updates, presence and subscriptions, so people working together see changes straight away.
Tracing, audits, drift signals and alerts that keep data accurate as usage grows.
How we deliver
4 phases, each ending with an output you can review.
We define the flows that must work offline, the data model, what syncs where and how correctness will be measured.
Output: Offline feasibility blueprint
We build durable local writes, indexing, optimistic UI and a plan for changing the schema later.
Output: Local data layer
We add queued operations, repeat-safe writes, retries, merge rules and replay.
Output: Sync and correctness engine
We add live updates, presence, tracing, audits and alerts, so data stays correct as you scale.
Output: Production-ready offline app
Your team
Specialists join your squad for this work, alongside a delivery lead who keeps you updated.
Designs durable local data models and schema changes, and keeps the app fast on weak connections.
Builds merge rules, versioning and replay that keep data correct across devices.
Builds streams, subscriptions, presence and fast connections tuned for real-world networks.
Runs monitoring, traces, failure analysis and alerts to keep data correct as you scale.
Trust and control
Every operation is traceable, with safe retries and replays that don't create duplicates.
Options for encryption at rest and guarded access to data stored on the device.
Trace IDs, audit logs and alerts catch sync problems early.
You keep full ownership of the code, configuration and documentation we create, with no vendor lock-in.
We pick what fits your product and team, not the other way round.
Results
We built a cross-platform app for a field-operations business. Staff receive jobs, capture photos and notes, collect signatures and update job status, and the app keeps working when the signal is poor.
We built a live dispatch and delivery platform for a growing logistics company. Operations teams and customers see driver status, job progress, location updates and delivery problems as they happen.
We built a live collaboration platform for a professional services business. Clients and delivery teams discuss work, share files, get updates and track project activity without long email chains.
We helped Eating All Together build a mobile nutrition app that combines personalised meal plans, ingredient scanning, grocery support and nearby dining suggestions in one place.
An offline-first app saves every action on the device first, then syncs with the server in the background. It works the same with or without a connection, and a lost signal only delays the sync. It suits field teams, drivers and anyone who works in places with patchy coverage.
Each change carries a version, and agreed merge rules decide the result when the same record changes on two devices. Where needed we use CRDT-style merging, which combines edits instead of letting the last one win. Silent overwrites are blocked, and conflicts are logged so they can be checked later.
The operation stays in the queue and is retried, with a growing gap between attempts. Because each operation is idempotent, a retry never creates a duplicate record. Failures are traced with a reason, alerts flag patterns early, and operations can be replayed in sequence to see exactly what happened.
We use WebSockets, subscriptions and event streams to push changes to every connected device as they happen, along with presence, so people can see who else is active. Fallbacks keep updates flowing when a connection is weak, and monitoring shows delivery problems before users report them.
We built a field workforce app where staff receive jobs, capture photos, notes and signatures, and keep working when connectivity is poor. We also built a live dispatch platform that shows driver status and delivery exceptions as they happen, and a live collaboration platform for a professional services business.
It depends on how many flows must work offline, how complex your data model is and how many devices share the same records. Sync and conflict rules need careful design, so we start with a review of your most important offline flow. A scoped project can kick off in 1–2 weeks.
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