Mobile App Development
Mobile App Development Built for the Years After Launch
Mobile app development for iOS and Android with offline behaviour, push, deep links and release automation handled properly, so shipping an update stays routine rather than becoming an event.
Hire a Dedicated Mobile Team
A look at what the numbers say about the team behind your build.
- 45+
- Engineers
- 50+
- Projects Deployed
- 10+
- Industries Worked In
- 2
- Development Facilities
- 10+
- Years of Experience
- 100+
- Happy Customers
- 24/7
- Support Availability
- 95%
- Client Retention
01 Trusted by
Apps we have shipped
From venture-backed startups to enterprise field tools, these are the apps we built and still release.
02 Capabilities
Mobile App Development Services
Mobile app development covers offline behaviour, notifications, release automation and monitoring. Those four decide whether an app survives its second year. We handle them during the build rather than after the first bad review, because every one of them is harder to add to an app already shipped.
What is an AI copilot?-
iOS & Android Delivery
One codebase where that serves the product and native where it does not, with the trade-off argued on your requirements rather than on our preference.
What is an AI copilot? -
Offline-First Behaviour
Local state, sync and conflict resolution designed up front, because a field app that needs a signal is a field app that gets abandoned.
What is an AI copilot? -
Push & Deep Links
Notifications and links that open the right screen in the right state, including cold start, the part that is always harder than it looks.
What is an AI copilot? -
Release Automation
Signing, build numbers, TestFlight and Play tracks automated, so a release is a pipeline run rather than an afternoon of ceremony.
What is an AI copilot? -
Crash & Performance Monitoring
Crash-free rate, startup time and ANRs tracked per release, with alerts, so a bad build is caught before the reviews arrive.
What is an AI copilot? -
Store Compliance
Privacy manifests, permission rationales, data disclosures and the review guidelines that cause most rejections, handled before submission.
What is an AI copilot?
03 Our process
How a Mobile App Development Build Runs
An app build runs in six steps, from scope through architecture, implementation and store submission, to an app live in both stores. Release automation is set up early, so shipping the second version costs a fraction of what shipping the first one did.
Get Started-
Discovery & Scope
We agree what the first release must do, what it deliberately will not, and how we will know it worked.
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Architecture & Design
Data model, integrations and interface designed together, so the build does not discover a constraint in week six.
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Build in Increments
Working software every sprint behind your own review process, with a demo you can click rather than a percentage.
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QA & Hardening
Automated coverage, load and security testing, and the unglamorous edge cases that decide whether launch week is calm.
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Launch
Staged rollout with monitoring and a rollback path, so going live is a controlled step rather than an event.
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Iterate & Support
Usage data drives the next sprint, and someone is accountable for uptime and response times after launch.
04 Industries
Mobile for Regulated Industries
Apps that meet the storage, consent and audit rules each sector already runs on.
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ITSM
Service-desk copilots that triage tickets and deflect L1/L2 volume, built and maintained by dedicated engineers in your existing tooling.
9+ Projects -
Legal
Contract and trust document review with retrieval over your own precedent library, cutting document review time by 60%.
6+ Projects -
Healthcare
Clinical documentation, intake, and patient records under HIPAA-compliant, auditable data flows, reducing documentation time by 40%.
10+ Projects -
Real Estate
Listing intelligence, valuation support, and agent workflows where search, updates, and coordination run continuously.
7+ Projects -
Construction
Estimating and field reporting connected to systems crews already use, delivered by dedicated teams who ramp into your stack.
8+ Projects -
Logistics
Dispatch, tracking, and exception handling where timing and visibility drive the operating decisions of the day.
6+ Projects
05 Case studies
Apps we have launched
Products in both stores, still shipping updates.
Change Management
AI-Powered Enterprise Change Management for Large-Scale Organizations
Enterprise change management software letting organisations execute, monitor and sustain change faster, with the progress of every initiative visible in one place.
Construction Management
Real-Time Construction Coordination, From HQ to Field
A construction coordination platform for multi site work, replacing spreadsheets and scattered email with tasks, schedules and on site progress synced in real time.
Legal & Estate Planning
Building a Secure, Multi-Portal Legal Platform
A digital estate planning platform running end to end across three portals, simplifying legal documentation and improving transparency for every party to a trust.
AI Based Real Estate Property
AI-Driven Property Insights Platform
Landwise NWA transforms commercial real estate workflows by providing AI-powered insights and data integration for faster decisions.
AI Automation
AI-Powered Content Automation Platform
An AI content engine that turns sales and strategy calls into ready-to-post content, matched to the brand's own voice and scheduled straight to LinkedIn.
06 Client review
Estimates matched the timeline.
Scope was set up front, the launch hit the milestone billing we agreed, and delivery matched what we were quoted.
Clutch
07 Tech stack
What we build apps with
The frameworks, platforms and tooling behind the apps we ship.
- OpenAI
- Claude
- Gemini
- Llama 3
- Mistral
- Falcon
- LangChain
- LlamaIndex
- Haystack
- DSPy
- LoRA
- PEFT
- Axolotl
- Unsloth
- Pinecone
- Weaviate
- pgvector
- Qdrant
- Chroma
- OpenAI API
- Anthropic API
- Vertex AI
- Bedrock
- LangSmith
- Langfuse
- Arize
- Helicone
- Guardrails AI
- NeMo Guardrails
- Presidio
- Streamlit
- Chainlit
- Next.js
- Vercel AI SDK
08 Challenges
What sinks a mobile build
Mobile builds sink when offline behaviour was an afterthought, when releases depend on one person and their laptop, or when crashes are only discovered through store reviews. We handle all three from the start, which is why updates stay routine instead of becoming events.
Rejected by review, twice
An app that needs a signal
Releases as an event
Deep links that open the wrong thing
No idea it is crashing
A prototype framework choice
09 Advantages
Why Teams Pick Us for Mobile App Development
Teams pick us for mobile because release automation, offline behaviour and crash monitoring are part of the build rather than a later project. Shipping an update should be something a team does on a Tuesday, not something it schedules and then worries about.
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Store Rules Handled Up Front
Privacy manifests, permissions, disclosures and deletion requirements are build tasks, not submission surprises. Fewer rejections, faster launches.
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Offline Designed, Not Retrofitted
Local state, sync and conflict resolution are decided in architecture, because this is the change that is genuinely expensive to make later.
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Releases Are Boring
Signing, versioning and store tracks automated from the first build, so shipping often is realistic and no single person is the release.
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Monitored Per Release
Crash-free rate, startup time and ANRs tracked with alerts, so a bad build is caught by us rather than by your reviews.
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The Stack Argued, Not Assumed
Cross-platform or native decided against your actual requirements, with the reasoning written down.
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Handed Over Cleanly
Your repo, your store accounts, documented pipelines, so your team can take over releases whenever it wants.
10 More services
What else we build
The rest of what we build, and the teams who build it.
- Business Process Automation We automate the repeatable parts of a process, from document intake to decisions and handoffs, with an exception path designed before the happy path.
- AI Consulting A short discovery that identifies high-impact use cases, reviews your data and systems, and returns a phased roadmap with costs and risks attached.
- AI Integration We wire AI into the systems you already run, with identity, data, latency and failure behaviour designed before anything ships.
- Chatbot Development Assistants that answer from your own content, hand off cleanly to a person, and log every conversation for review.
- Generative AI Consulting A short engagement that finds where generative AI pays for itself in your business, and where it does not.
- Generative AI Development We design and integrate large language model features into your product, with retrieval, evaluation harnesses, and prompt governance in place before launch.
- AI Agent Development Assistants and autonomous agents that work inside your systems, handling support, intake, and internal workflows with human handoff where it matters.
- IT Staff Augmentation Senior engineers who join your sprints, tools, and review process, so capacity goes up without your team losing control of priorities.
- AI Copilot Development Copilots built into your product, so the assistant works where your users already are rather than in a separate window.
- Machine Learning Development Forecasting, classification, and computer vision models trained on your data, deployed with monitoring so accuracy is measured rather than assumed.
- Machine Learning Consulting An assessment of whether the signal you need exists in your data, and what a model would actually be worth.
- SaaS Development Multi-tenant products built to be sold: billing, permissions, onboarding and the operational work that comes after launch.
11 FAQ
Frequently asked questions
The things teams ask before starting with us.
Mobile app development includes offline behaviour, notifications, release automation and crash monitoring, all handled during the build. Those four decide whether an app survives its second year, and every one of them is far harder to add once the app has already shipped.
It depends on what the app has to do, and we argue it from your requirements rather than a default. Cross-platform wins for most business and content apps and roughly halves the cost. Native wins where you need deep platform integration, heavy graphics, background processing or the newest OS features on day one. We put the trade-off in writing during discovery so the choice is yours.
Yes, including the parts that cause rejections: privacy manifests, permission rationales, data disclosures and account deletion. We set up the pipelines and can submit on your behalf or hand the process to your team documented. The accounts and certificates stay yours throughout.
We start with a short discovery call to clarify goals, constraints, and success metrics. Then we identify high-impact AI use cases, review your data and systems, and propose a phased roadmap with costs and risks attached to each phase.
Discovery runs 2 to 4 weeks, an MVP typically lands in 8 to 16 weeks of weekly-demo sprints, and operate is an ongoing arrangement with monitoring and support after launch.
Fixed-scope work is priced per milestone, dedicated teams are billed monthly per seat, and staff augmentation is weekly or monthly. You pick the model that fits and can switch between phases. There is a fuller breakdown of what moves the number on our AI development cost page.
You do. The full repository, documentation, and deployment transfer to you at every milestone, with no lock-in to us.
NDAs from day one, scoped access, and data residency decided at the architecture stage. We work within HIPAA, SOC 2, and similar requirements where they apply.
We monitor accuracy, cost, and uptime, run regression checks as models drift, and keep a defined escalation path with support so the system stays healthy after release.
12 Book a Call
Ready to scope your app?
Tell us where you are and what has to be true for this to work. We come back with an approach, a timeline and a number.
- 2451 West Grapevine Mills Circle, Grapevine, TX 76051 · USA
- hello@kodertal.com
- Reply within 1 business day, 24/7 support once live
