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AI development services
We design, build and ship AI your team will actually use — assistants, agents, document intelligence and predictive models — connected to the products and data you already have.
Models & platforms we build with
What we build
Not a generic chatbot bolted on — AI designed for a specific job in your business, connected to your data and measured on results.
Assistants that know your products, policies and customers — on your website, in your app or inside your team’s tools.
Ask a question, get an answer drawn from your own documents, wikis and databases — with the sources linked.
Agents that carry out multi-step work across your systems — and ask for approval before anything important.
Turn invoices, contracts, forms and scans into clean, structured data your software can use straight away.
Models that forecast demand, spot churn and fraud, and recommend the next best action from your data.
Add AI features to the web or mobile app you already run — built by the same team that builds Laravel, React and React Native apps.
How we deliver
A clear path that proves value early, then builds it properly — so you never pay for AI that only works in a demo.
We map the workflow, the data you have and where AI genuinely pays off.
You get: A scoped use case with clear success measuresA working proof of concept on your real data, tried by real users.
You get: A demo you can test, not slidesProduction code wired into your apps, APIs, permissions and data.
You get: AI that lives inside your productTest suites, guardrails and human review before anything goes live.
You get: Measured quality and safetyMonitoring, cost tracking and continuous tuning after release.
You get: AI that keeps getting betterWhere it helps
A few of the ways AI is saving teams time and money in the sectors we work in most.
Collects symptoms and history before the visit and drafts a summary for the clinician.
AI assistantTurns long reports and discharge notes into clear, plain-language summaries.
Document intelligenceFlags appointments likely to be missed and sends well-timed reminders.
Predictive modelAnswers product questions and recommends items straight from your catalogue.
AI assistantWrites titles, descriptions and SEO copy in your brand voice.
Content generationPredicts stock needs per product and season to cut stock-outs and overstock.
Predictive modelReads IDs, bank statements and invoices into structured, verified data.
Document intelligenceSurfaces unusual transactions for your analysts to review first.
Predictive modelAnswers account questions with replies that cite your policies.
Knowledge searchExplains concepts step by step, at each learner’s own level and pace.
AI assistantBuilds quizzes and marking rubrics from your course material.
Content generationSpots learners likely to drop out early enough to help them.
Predictive modelPredicts arrival times and warns customers before a delay hits.
Predictive modelReads bills of lading, customs forms and delivery notes automatically.
Document intelligenceAnswers “where is order 4821?” across every system in one place.
Knowledge searchTurns property details and photos into polished listings in seconds.
Content generationQualifies enquiries around the clock and books viewings into your calendar.
AI assistantSuggests a price range from comparable properties and market trends.
Predictive modelWorking in another industry? Tell us about your workflow
Quick check
Think of one task you'd like AI to take on and tick what's true for it. It takes thirty seconds and shows where a project would start.
Each point is something that helps an AI project succeed. The strongest first projects usually tick four or five.
A few pieces are in place. A short discovery phase will show whether AI, simple automation or better data is the right fix — before you spend on a build.
Suggested first stepDiscovery · 1–2 weeks
Most of what an AI project needs is there. Discovery pins down the data and how success is measured, then a prototype proves it on real cases.
Suggested first stepDiscovery, then a prototype
This is the kind of task AI handles well. A prototype on your own data is a sensible first step, so you see it working before committing to a full build.
Suggested first stepPrototype · 2–4 weeks
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FAQ
Straight answers on timelines, data privacy, models and running costs.
Tell us what you're planning and our team will reply within 24 hours.
Contact UsDiscovery takes 1–2 weeks and a working prototype on your real data another 2–4, so you see results within the first month or so. The production build then usually takes 6–12 weeks, depending on the use case and how many systems it connects to — and we plan it from what the prototype teaches us.
No. We set projects up with enterprise API settings that exclude your data from model training, or host open-source models in your own cloud when data must stay in-house.
OpenAI, Anthropic Claude, Google Gemini, and open-source models such as Llama and Mistral. We pick the model for each task based on quality, speed, cost and privacy needs — and can switch later without a rebuild.
Yes. Most of our AI work plugs into existing products — Laravel, Node.js, Python, React and React Native apps — through clean APIs, so you don’t need to rebuild what already works.
We ground answers in your own data (RAG) with source citations, test every release against real examples, add guardrails for sensitive topics, and keep a person in the loop wherever an action matters.
Running costs depend on usage and the model. We estimate monthly costs up front and keep them down with caching, smaller models for simple tasks and routing to larger models only when needed.
Let's discuss your project requirements and get expert advice from our team.
Let's discuss your project requirements. Get expert advice from our team — free initial consultation.
Enquire about our services
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Discuss your project requirements with experts.
Based on your requirements, we create a proposal.
Danny Lalwani
Founder and Technical Lead at CodiFly
Ashish Kharloya
Founder and Technical Lead at CodiFly