AI Agent Development
As an AI agent development company, we build systems that move past demos: autonomous AI agents that take real actions, retrieval-augmented generation (RAG) pipelines tuned on your data, and evaluation harnesses that keep quality from drifting in production.
Most AI projects die in the gap between a clever demo and a system you can put in front of customers. We close that gap. As an AI agent development company, Malgary Labs builds production AI — autonomous agents that take real actions, retrieval-augmented generation (RAG) pipelines grounded in your data, and the evaluation infrastructure that keeps quality from drifting once real users arrive.
Every engagement is led by a senior engineer who writes the code — no offshoring, no juniors hiding behind senior names. We are model- and framework-agnostic: we build on OpenAI, Anthropic, or open-source models and wire agents to your tools and APIs, choosing the stack for your real constraints around latency, cost, and data privacy rather than chasing hype.
Reliability is the hard part of agents, so we treat it as a first-class deliverable. Every build ships with an evaluation harness tied to real examples, observability so you can see what an agent did and why, and human-in-the-loop checkpoints where decisions carry risk. Changes are gated behind regression tests, so quality is measured — not hoped for.
Whether you need a single-flow agent prototype to validate an idea in a week, or a multi-month build of an agent platform with guardrails and cost controls at scale, we scope it honestly and ship working software at every milestone. You own 100% of the code and IP at the end.
What we cover.
- LLM application engineering (OpenAI, Anthropic, open-source)
- Agentic systems & tool-use orchestration
- Retrieval-Augmented Generation (RAG) pipelines
- Fine-tuning & evaluation infrastructure
- Computer vision & multimodal systems
- AI product strategy & technical due diligence
What we build with it.
Customer-support agents
Agents that resolve tickets end-to-end — reading your knowledge base, taking actions in your systems, and escalating to a human with full context when they should.
Internal copilots
Domain-specific assistants that let your team query data, draft documents, and trigger workflows in plain language, grounded in your own sources.
RAG over private data
Retrieval pipelines tuned on your documents, tickets, and databases so answers are accurate, current, and cite their sources.
Document & data extraction
Multimodal pipelines that turn PDFs, forms, and images into structured, validated data your systems can actually use.
Workflow automation agents
Agents that orchestrate multi-step processes across your tools with tool-use, retries, and audit logs you can trust.
AI strategy & due diligence
Technical assessments for founders and investors — what is feasible, what it costs, and what breaks at scale.
Rabt360 — AI-assisted operations platform
We replaced paper forms and spreadsheets with one platform that parses quotation PDFs into structured project records and flags overdue jobs, low stock, and delivery delays before they slip.
How we work together.
7-Day Sprint
Fixed-price one-week build. Best for validation and prototypes.
Project Build
Multi-week, fixed scope. Weekly demos, working code at every milestone.
Embedded
Senior engineers join your team on a monthly retainer.
AI agent prototypes start in the $8,000–$25,000 range via our 7-Day MVP Sprint. Production agent platforms are scoped and quoted on a free consultation — a fixed price, in writing, before any work begins.
Common questions.
How much does it cost to build an AI agent?
It depends on scope. A single-flow agent prototype in our 7-Day MVP Sprint typically lands between $8,000 and $25,000. Full production agent platforms with evals, guardrails, and integrations are quoted on scope after a free consultation — usually a multi-week engagement. You always get a fixed price in writing before any work starts.
What frameworks and models do you use?
We are model- and framework-agnostic. We build on OpenAI, Anthropic, and open-source models, and use tools like LangChain, LlamaIndex, and custom orchestration depending on the job. We pick the stack for your constraints — latency, cost, privacy — not the other way round.
How long does it take to build an AI agent?
A validated single-flow agent ships in 7 days through our sprint. A production-grade agent or platform usually takes a few weeks to a few months depending on integrations and reliability requirements. We give you a realistic timeline before we start.
What is the difference between an AI agent and a chatbot?
A chatbot answers questions. An agent takes actions — it calls your APIs, uses tools, makes decisions across multiple steps, and completes a task end-to-end. We build agents with tool-use, retries, and human-in-the-loop checkpoints so they are safe to run in production.
How do you keep AI quality from drifting in production?
Every build ships with an evaluation harness tied to real examples, plus observability so you can see what the agent did and why. Changes are gated behind regression tests, so quality is measured, not assumed.
Do we own the code and models?
Yes — you own 100% of the code and IP. It lives in your repository and runs in your cloud accounts. We hand over everything with documentation and a recorded walkthrough.
Can you work with our existing team?
Yes. Beyond fixed-scope builds, our senior engineers can embed with your team on a monthly retainer to ship alongside your in-house engineers.
Got an idea worth building?
Book a free 30-minute consultation. We will scope it, price it, and tell you honestly whether we can deliver — or who can.