AI Solutions
Practical AI Built on Your Data,
Your Cloud, Your Terms
We build AI that delivers real results — not experiments. RAG systems, AI agents, document processing, and predictive models, deployed on your own infrastructure with clean data underneath.
Why Most AI Projects Fail to Deliver
Built on top of messy data
AI is only as good as the data it runs on. Most projects fail not because of the model — but because the underlying data is inconsistent, incomplete, or unstructured.
Experiments without a clear ROI
Proof-of-concept projects that never make it to production. Impressive demos that don't translate to time saved or revenue generated.
Vendor lock-in and data exposure
SaaS AI tools charge per seat, per query, or per document — and your business data flows through their servers. Costs scale unpredictably and data governance becomes a concern.
Our Advantage
AI That Works Because the Data Works First
We are one of the few teams that delivers the full stack — data warehouse, analytics layer, and AI on top. Most AI consultants inherit bad data and work around it. We fix it at the source.
Data Warehouse
Clean, structured, unified data foundation
Analytics Layer
Metrics, models, and business logic
AI Layer
RAG, agents, predictive models on clean data
Deployed to Your Cloud
AWS, Azure, or GCP — owned by you
What We Build
Practical AI applications with clear ROI — scoped to your specific workflow, not generic use cases.
RAG Systems
Let your team query internal documents, contracts, policies, or knowledge bases in plain English. The AI finds and synthesises the answer — no manual searching.
AI Agents
Automated query handling, routing, and task execution. Agents that can take action — not just generate text — integrated into your existing workflows.
Document AI
Automated extraction from invoices, contracts, and forms. Data pulled, validated, and pushed to the right system — without anyone opening the document.
Internal Chatbots
Staff-facing assistants trained on your internal knowledge — HR policies, product documentation, SOPs. Instant answers, consistent information.
Predictive Models
Revenue forecasting, churn risk, demand prediction, lead scoring — machine learning models built on your historical data using scikit-learn and Python.
AI-Assisted Reporting
Natural language interfaces on top of your data warehouse. Ask a question in plain English, get a dashboard or summary — no SQL required.
Models & Frameworks We Work With
We are model agnostic. We choose based on your use case, data sensitivity, and cost — not preference.
AI Models
OpenAI/GPT, Anthropic/Claude, Llama, Mistral
Deployment Platforms
AWS Bedrock, Azure OpenAI, self-hosted open-source
AI Frameworks
LangChain, LlamaIndex, Hugging Face, NLTK
ML & Data Science
scikit-learn, Python, pandas, NumPy
Model Serving
FastAPI — production-ready API endpoints for your AI models
Infrastructure
AWS (primary), Azure, GCP — everything deployed to your account
How We Work Differently
ROI before build
We identify a specific, measurable problem first. We define what success looks like and validate the approach before committing to a full build.
Model agnostic
No preferred vendor, no referral arrangement. We recommend the right model for your use case — including open-source where it makes more sense than a paid API.
Your cloud, your data
Where data sensitivity requires it, we deploy fully within your AWS, Azure, or GCP environment. Nothing leaves your infrastructure.
Full stack if you need it
We can deliver the data warehouse, analytics layer, and AI on top — or just the AI layer if your data is already ready. End-to-end or targeted, your choice.
AI Consulting for SMBs Across Canada and the US
We work best with businesses that have a specific, high-volume problem that AI can genuinely solve — not those chasing the technology for its own sake.
- ✓ Teams processing large volumes of documents — invoices, contracts, forms — that require manual review today
- ✓ Businesses wanting to make their internal knowledge searchable and queryable without building a dev team
- ✓ Operations teams who need automated query handling, routing, or classification at scale
- ✓ Companies with clean historical data who want to add forecasting or predictive scoring
- ✓ Businesses who have been burned by AI experiments that never made it to production
Frequently Asked Questions
Which AI models do you work with?
We are model agnostic. We work with OpenAI/GPT, Anthropic/Claude, and open-source models including Llama and Mistral via AWS Bedrock, Azure OpenAI, or self-hosted deployments. We recommend the right model based on your use case, data sensitivity, and cost requirements.
Does our data leave our environment?
That depends on the model choice — and we discuss it explicitly with every client. Where data sensitivity is a concern, we deploy open-source models in your own cloud environment so your data never leaves your infrastructure. Where third-party APIs are appropriate, we ensure your data handling meets your requirements.
What is a RAG system and do we need one?
RAG (Retrieval-Augmented Generation) lets an AI model answer questions using your own documents and data — not just its training data. It's the technology behind internal chatbots, document search, and knowledge base Q&A. If your team spends time manually searching for information or answering the same questions repeatedly, a RAG system is likely a good fit.
What makes your AI work different from buying an AI SaaS tool?
Off-the-shelf AI tools are built for the average use case. We build to your specific data, your workflows, and your business logic — deployed on your infrastructure with no per-seat or usage fees to a third party. You own everything we build.
Do we need a clean data warehouse before you can build AI?
For AI that relies on your business data — predictive models, analytics AI, forecasting — yes, clean structured data is essential. We offer end-to-end delivery: data warehouse, analytics layer, then AI on top. If your data is already in good shape, we can build the AI layer directly.
How do you approach AI projects to make sure they deliver ROI?
We start by identifying a specific, measurable problem — not a technology to explore. We scope the smallest solution that solves it, validate the approach before committing to a full build, and define success metrics upfront. We have no interest in AI projects that look impressive but don't move your business forward.
Have a specific problem AI might solve?
Book a free 30-minute call. We'll tell you honestly whether AI is the right solution — and what it would actually take to build it.
Book a Discovery Call