AI model integration and evaluation
We source, evaluate, and connect capable models to real products, including vision, multimodal workflows, and structured outputs.
AI systems from data to deployment
We collect the data, build the intelligence, and ship the product—RAG, agents, voice, automation, and full-stack software for ambitious teams.
Why Wizardry Labs?
Based in DHA Karachi, Wizardry Labs is an AI software development agency for teams that need useful systems, not just impressive demos.
We work across the stack: collecting and structuring difficult data, adapting models to real workflows, grounding systems with RAG, and shipping the interfaces people actually use.
Our work combines research depth with product pragmatism for companies, institutions, and teams building what comes next.
Built for complex work
Selected products
View all workData platformsRAGAgents
Food Intelligence
A national restaurant and menu intelligence platform that collects, normalizes, and retrieves food data so people can discover meals and order from the platforms that serve them.
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ModelsRAGAgents
Wizardry Models
A model and AI systems platform for giving teams access to capable models, APIs, vision, fine-tuning, RAG, agents, and voice workflows.
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Good AI is not a demo. It is a system that understands context, fits the workflow, and earns trust.
Wizardry Labs
AI systems, data, and product engineering
Our expertise
RAG and knowledge systems
We turn company and public data into grounded search, retrieval, and answer systems that can explain where their context came from.
AI agents, automation, and MCP tools
We build agents that can reason, call tools, and move work through business, institutional, and government systems.
Model adaptation and fine-tuning
We shape models for specific domains with prompt engineering, evaluation, fine-tuning, and careful data preparation.
Data collection and intelligence platforms
We collect, normalize, enrich, and index difficult data so products can search it, understand it, and keep it fresh.
Voice and conversational interfaces
We design chat, voice, and Siri-like interfaces that can understand requests and take useful action.
Low-level inference and model optimization
We explore GGUF, quantization, KV-cache management, C/C++, Metal, and Apple Silicon for efficient local inference.
Full-stack product engineering
We ship the web, macOS, API, cloud, and MLOps layers that turn an AI capability into a dependable product.
Recent insights
Notes from building models, data systems, and AI products in the real world.
AILLMOpsInference
KV-cache management under memory pressure
A practical look at active KV-cache limits, paging, and the tradeoffs behind longer conversations on constrained hardware.
AIInferenceMetal
Layer streaming on Apple Silicon
Model weights do not all need to be equally hot. Layer-aware prefetching and eviction can give a local runtime more room to work.