AI & Machine Learning Development
We build AI products that ship, not lab demos that wow in a meeting and never reach production. From LLM powered features inside your app to custom ML pipelines, our team takes you from idea to evaluated, monitored, revenue earning AI.
- Replies inside 1 business day
- Fixed-scope or retainer engagements
- Teams in Canada and Nigeria
Why teams pick us
AI features that survive contact with real users
A weekend demo with a free API key is easy. AI that handles real traffic, respects your data and stays inside a budget is what we do. Our engineers treat AI as software engineering with extra steps, not magic.
40%+
Inference cost saved
After first optimisation pass
<2 wk
Prototype to demo
On most LLM features
100%
Outputs evaluated
Versioned eval sets
0
Prompt only releases
Every change is measured
Why Dafe Software
What you get when you work with us
Production from day one
Every AI feature we build comes with evaluations, observability, fall backs and a cost budget. No prototypes pretending to be products.
Your data stays yours
We design for data privacy, regional residency and zero retention with the providers that support it. Audit ready by design.
Vendor and model agnostic
OpenAI, Anthropic, Google, Mistral, open weights via Llama. We pick the model that fits the use case, not the one with the loudest marketing.
Evaluated, not vibed
Every output path has a written evaluation set, scored on every release. Quality is a number, not a feeling.
Cost engineered
We instrument every token. Most clients save 40% or more after our first cost pass without losing quality.
Senior engineering
Our AI work is led by engineers who built ML systems before ChatGPT, not by hobbyists who finished a 12 week bootcamp last year.
What we deliver
AI & Machine Learning Development we ship every quarter
LLM powered product features
Chat, drafting, summarisation, classification, structured extraction and routing inside your existing product.
RAG & knowledge assistants
Retrieval augmented generation over your docs, support tickets, code or contracts, with citations and access controls.
AI agents & automation
Multi step agents that handle real workflows like research, scheduling and back office tasks, with humans on the loop where it matters.
Custom ML models
Forecasting, recommendation, anomaly detection and computer vision models, packaged as APIs your team can consume.
Fine tuning & evaluation
SFT, LoRA and DPO on open models when you need them, with proper eval harnesses to prove the win.
MLOps & infrastructure
Inference servers, vector databases, feature stores, observability and cost dashboards on AWS, GCP or Azure.
How we work
A process built for shipping, not stalling
Use case discovery
We sit with your team to find the one or two AI features that will actually move a business metric. The rest stays in the parking lot.
Prototype & evaluate
Two week proof of concept with a written eval set. You see real numbers, not cherry picked demos.
Production engineering
We harden the prototype with auth, rate limiting, caching, monitoring, fall backs and cost controls.
Operate & improve
Weekly eval runs, monthly cost reviews and a roadmap of model and prompt improvements.
Tech stack
Tools we lean on for ai & machine learning development
Start the conversation
Two ways to talk to us about your ai & machine learning development
Send a written brief and we will reply with a real plan, or grab a free 30 minute call on our calendar. Whichever is faster for you.
- Reply within 1 business day, every time
- Senior engineer on the first call, not a sales rep
- No pressure, no hard sell, no recurring nudges
Project Inquiry
Tell us about the AI feature or product you want to build
Share a short brief. A senior AI engineer will reply within one business day with an honest assessment, a price range and a realistic timeline.
Common questions
Frequently asked
How do you handle our private data?+
We use zero retention endpoints where available, design with regional residency in mind and can fully self host on open weights when policy requires it. Every project starts with a written data flow.
Can you fine tune a model on our data?+
Yes. We will only recommend it after exhausting prompt engineering and RAG, because fine tuning is expensive to maintain. When it is the right call, we have shipped it before.
How much does an AI feature cost to run?+
It depends on traffic and model choice. We give you a per request cost estimate before we ship, plus a monthly cost dashboard once it is live.
Do you work with non technical teams?+
Often. We translate between leadership, product and engineering, and we will write the eval criteria with your domain experts, not just from the developer side.
