AI & Blockchain Development
- Lahore--:--
- Dubai--:--
Technology without limits, innovation without boundaries, results that matter.
AI Development. Blockchain Solutions. Built to Scale.
- 100+
- Projects shipped
- 50+
- Engineers
- 2022
- Williams F1 livery
Full-Stack Technology Development Services
Custom machine learning models, LLM integration, and predictive analytics built for production rather than for demos. We architect systems that automate workflows and surface insight from your data, and stay with them from preparation through deployment and ongoing tuning.
Included
- Model training & evaluation
- LLM and RAG integration
- Deployment & MLOps
- Monitoring and retraining
Secure, audited smart contracts and decentralised applications across major chains. We handle protocol design, contract implementation, and the audit cycle, then build the interfaces your users actually touch.
Included
- Protocol & contract design
- Audit preparation
- dApp front ends
- Indexing and subgraphs
Infrastructure for issuing and managing tokenized real-world and digital assets. We build the issuance, custody, and transfer rails, and design them around the compliance constraints of your jurisdiction rather than retrofitting them later.
Included
- Token standards & issuance
- Custody integration
- Compliance workflows
- Secondary transfer rails
Immersive experiences and games for web, mobile, and headset platforms. We take a concept from prototype to shipped build, covering engine work, the art pipeline, and platform certification.
Included
- Unity & Unreal builds
- WebXR experiences
- Art and asset pipeline
- Store submission
Bespoke platforms built around how your business actually works. We start with the workflow rather than the feature list, and deliver a system your team can operate and extend without us.
Included
- Product & technical discovery
- Platform architecture
- Web and mobile applications
- Handover & documentation
Strategy, architecture review, and hands-on guidance from a senior engineering team. Useful when you already have engineers and need the direction settled before the build starts.
Included
- Architecture review
- Technology selection
- Team & delivery planning
- Ongoing advisory
Teaching and training environments built for headsets rather than ported to them. We build the room, the lesson that runs inside it, and the simulation a trainee can get wrong safely — for classrooms, laboratories, orientations, and conferences that need people in the same space without being in the same place.
Included
- Virtual classrooms & lecture halls
- Virtual lab environments
- Training simulations
- Orientations & onboarding
Our Philosophy
- 01AI-Driven
We use what we build.
- 02Security-First
Protection before deployment.
- 03Transparency Always
No surprises, ever.
- 04Build to Scale
Architected for 10x growth.
- 05Partnership Over Projects
Clients return, always.
- OpenAI
- Anthropic
- Google Gemini
- PyTorch
- TensorFlow
- LangChain
- LlamaIndex
- Vector databases
- Ethereum
- Solidity
- Rust
- IPFS
- Swift
- Objective-C
- Python
- Node.js
- C#
- C++
- Kotlin
- JavaScript
- React
- Angular
- ARCore
- ARKit
- Oculus SDK
- Android SDK
- Unity 3D
- Unreal Engine
- AWS
- Google Cloud
- Azure
Don't take our word for the 3D
Three avatars from the vFlects line, on our own Sketchfab account. Load one and drag to orbit it — that is the shipped rig turning, not a render of it.
The line is published in full at sketchfab.com/BiMDemo
2022 · Japanese Grand Prix · Suzuka
Featured on Williams Racing F1 Car
Big Immersive became the first Pakistani tech company to appear on a Formula 1 car at the 2022 Japanese Grand Prix.
- Pakistani tech on F1
- 1st
- Circuit
- Suzuka
- Season
- 2022
Frequently Asked Questions
Have some questions? We have the answers.
5 answered
Most AI projects take 3-9 months from discovery to deployment. MVPs with core functionality are possible in 8-12 weeks. Complex enterprise implementations may require 6-12 months.
We build on the major model providers — OpenAI, Anthropic, and Google Gemini — and train in PyTorch and TensorFlow where a project needs its own model rather than a general one. Around them we use LangChain and LlamaIndex for orchestration and retrieval, with a vector database behind them. Which combination we reach for depends on your performance, cost, and deployment constraints.
We build on Ethereum and EVM-compatible networks, and on purpose-built Layer-1s where a project needs its own chain rather than a shared one. Contracts are written in Solidity, with Rust where the target chain calls for it, and we use IPFS for off-chain assets. We select the network that matches your throughput, cost, and ecosystem needs.
We follow a discovery-first process: scoping and research, architecture and design, iterative build sprints with regular demos, rigorous testing, and a supported deployment with post-launch monitoring.
We work in short, reviewable milestones so you see progress continuously and can course-correct early. We don't consider a milestone done until it meets the agreed acceptance criteria.