Services
We design and implement end-to-end AI solutions tailored to your organization's needs: practical, cost-effective systems that create measurable improvements in productivity.
Contact us for AI implementation inquiries, we'd be happy to chat.
Contact UsOur Work
Retrieving information from an SQL database requires specialized knowledge of writing SQL code. For one Vancouver-based communications company, this meant every data request had to go through a single IT staff member, creating delays and pulling that person away from other work.
We built a natural language querying system that allows anybody, regardless of technical skill level, to retrieve database information using plain English. A user can ask something like “what were our top 5 customers by revenue this quarter,” and a locally hosted AI model translates the question into SQL, runs the query, and returns the results in a clean, readable format. Users can also save queries to rerun automatically later.
The system was deployed on a physical server inside the client's own server room, running the AI model locally so no data or schema ever left their network. We tuned the model to the company's specific schema and terminology, with a working version delivered in a matter of weeks.
This project turned a technical bottleneck into direct, self-service access to business data, and shows our ability to implement AI in real environments with real data and real infrastructure constraints.
A company was running its entire operation, customers, inventory, sales, and rental orders, on a legacy system over 20 years old. The system was slow and unintuitive, requiring users to learn workarounds just to navigate basic tasks. It was also error-prone, and mistakes in the workflow sometimes resulted in missed billings and lost revenue.
We built a modern, web-based platform to replace the legacy system entirely, covering sales, work, and rental orders, serial number scanning and tracking, pricing management, customer records, and reporting. The system was developed collaboratively with the client's team, with real user feedback shaping features throughout an iterative rollout.
The platform was built with SQL, Node.js, Python, JavaScript, HTML, CSS, and Tailwind, with full authentication and authorization built in. Development was iterative, with features refined and added based on direct feedback from the people using the system daily.
This project replaced a two-decade-old system with a modern platform built around how the team actually works, cutting errors, speeding up operations, and doing it at a fraction of competitor pricing.
A North Vancouver company suspected revenue was slipping through the cracks, but had no practical way to check other than manually reviewing thousands of orders. Reconstructing what actually happened on an order meant manually cross-referencing order records, billing notes, customer correspondence, and internal staff discussion.
We deployed 15 AI agents to work through a year of order data in parallel, each one reviewing the full context of an order, not just the invoice, to check whether billing matched what actually happened. When something looked off, such as a billed duration that didn't match the correspondence, the agent flagged it along with the reasoning and supporting evidence behind the flag.
The agents pulled data directly from the client's CRM and ERP systems alongside billing notes and correspondence, allowing each order to be reasoned through the way an experienced billing clerk would, but at far greater scale. Data handling was tailored to the client's security needs, with options ranging from private inference to a fully onsite deployment.
A single day of AI-driven analysis turned a suspected problem into a concrete, evidence-backed list of recoverable revenue, showing how AI can find what manual review never could.
Employees often spend valuable time digging through folders, PDFs, and reports just to locate a single piece of information needed to complete a task. As internal documentation grows across standards, project files, and emails, that time adds up and slows down everyday work.
We built an LLM-powered knowledge assistant that ingests a company's internal documentation and lets employees ask questions in natural language, similar to ChatGPT, but trained entirely on their own data. Instead of keyword matching, the system understands context across standards, project documents, and correspondence, and returns precise answers with clickable source references linking directly to the exact section of the original document.
The system is built around complex vector embeddings to determine relevant sources with precision, and is configured specifically to a company's internal documents, processes, and terminology. It can be sized for large document volumes and deployed locally when a project requires tighter control over data.
For document-heavy organizations, this tool turns scattered internal knowledge into something employees can simply ask questions of and trust. If your team is losing time searching for information you already have, we would be happy to talk through what this could look like for your organization.
Browse the full set of AI systems we've delivered, with walkthroughs and case studies.
View Our WorkHow We Work
We work closely with your team to understand your operations, technical environment, and business objectives to clearly define the problem and identify the most effective AI approach.
Our team designs and develops a custom AI system tailored to your workflows, data, and infrastructure.
The solution is rigorously tested and refined through feedback to ensure reliability, accuracy, and usability.
Once validated, the solution is deployed into your production environment and integrated with your existing systems.
We provide ongoing monitoring, optimization, and support to ensure your AI systems continue delivering value as your business evolves.
Our team combines expertise in AI, software development, and information systems to build solutions that improve operational performance and deliver real business results.
Timelines
As a small, focused, local team, we pride ourselves on responsiveness, speed, and cost effectiveness. Compare that to many competitors: large, slow moving organizations often based in a different country or continent, with layers of process between you and the people doing the work.
Being small and local means we work closely and collaboratively with you, so we can deliver quality solutions quickly, without the overhead.
Every AI implementation is scoped to your business needs. Contact us for a detailed quotation.
Part of the cost may not need to come out of pocket. Federal and BC programs such as BDC LIFT and PacifiCan's Regional Artificial Intelligence Initiative fund AI implementation for eligible businesses. Check which AI grants and loans your business may qualify for.
What You Get
After a successful AI implementation project, you'll have a working system that meets the agreed upon project scope, has incorporated feedback from users during testing, and is actively being used by your staff, along with the resources needed for training and day to day usage.
The specifics of deliverables and ownership are worked out during the quoting stage, since every project scope is different. Typical items we discuss at that stage include:
This ensures both sides are clear on what's included, and what's optional, before work begins.
Security
We take data privacy seriously, and we make sure you understand exactly how your information is handled before any implementation begins. Most AI tools, including popular options like ChatGPT and Claude, process your data on third party servers. For most use cases this is a safe and practical choice, but businesses handling sensitive client, patient, financial, or legal information often want more control over where their data goes.
That's why we also offer on-site AI deployment for businesses where data security is a top priority. With an on-site setup, AI runs on hardware located in your own building, so information never leaves your network. This gives you full control over your data, protection from third party outages or policy changes, and predictable long-term costs, with the trade-off of a higher upfront investment and a system that's slightly behind the very newest cloud models.
Every project starts with a conversation about your specific needs, including how sensitive your data is and what compliance requirements you may have. From there, we help you decide whether a cloud based solution, an on-site deployment, or a hybrid approach is the right fit, and walk you through the trade-offs so you can make an informed decision.
Tell us what you're trying to improve and we'll walk you through what an AI implementation could look like for your business.
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