AI Solutions
We design and implement AI solutions that automate repetitive work, improve customer experiences, and connect the systems a business already depends on, with the software and ERP capability to deliver them properly.
Our Approach
Most AI projects fail at the same point: the demo works, and then it meets the business. Real catalogues are inconsistent, real customers ask questions the documentation does not cover, and real systems have to reconcile with finance at the end of the month.
We have spent more than a decade implementing ERP, integrating business systems, and documenting technical work to a standard that withstands CRA review. That is the same discipline an AI system needs to be trusted with anything that matters. We build AI into the processes you already run, and we are candid about the work it is not ready to do.
Selected Work
Home Theater Seating · E-Commerce
Product content generation · SEO metadata · Attribute extraction · Workflow automation
Challenge
Valencia's catalogue covers a wide range of seating configurations, each with its own materials, dimensions, motion features, and layout options. Writing listing content for every variant, then keeping it accurate as the range changes, is slow manual work that competes with the rest of the merchandising schedule.
Solution
We designed an AI-assisted content workflow that reads structured product specifications and produces listing copy, metadata, and search-oriented content in a consistent brand voice. Product attributes are extracted from the source specification rather than re-entered by hand, so a configuration change flows through to the content that depends on it.
Outcome
Less manual copywriting for each configuration, more consistent product information across the catalogue, and a repeatable way to add products without adding a proportional amount of content work.
Furniture Retail · Direct-to-Consumer
Conversational assistant · Product discovery · FAQ automation · Conversation routing · Lead capture
Challenge
Finn & Form sells leather and fabric furniture across a deep range of sofas, sectionals, chairs, dining sets, and beds. Shoppers ask the same questions repeatedly about materials, dimensions, configuration, and delivery, and those questions arrive at every hour across two countries.
Solution
We built an AI assistant that answers product and policy questions from the company's own product information, helps shoppers narrow down configurations from what they describe, and hands the conversation to a person when a question needs one. Context gathered during the conversation carries across, so the team picks up with the detail already in hand.
Outcome
Faster answers for shoppers outside staffed hours, less repetitive handling of routine enquiries, and a consistent account of product detail regardless of who or what answers first.
B2B Sales Technology · SaaS
Lead discovery · Data enrichment · Lead scoring · Outreach personalization · CRM integration
Challenge
Prospecting at scale means finding the right companies, learning enough about each one to say something relevant, and deciding which are worth a salesperson's time. Done by hand, the research is the bottleneck, and quality drops as volume rises.
Solution
We developed an AI-driven workflow that identifies prospects against a defined customer profile, enriches each record from available sources, scores it against qualification criteria, and drafts outreach grounded in what the research actually found. Qualified prospects and their supporting context move into the sales process rather than sitting in a spreadsheet.
Outcome
Research effort concentrated on prospects that fit, a consistent qualification standard applied across the pipeline, and outreach that reflects real detail about each company rather than a generic template.
Capabilities
Four areas where we see AI deliver measurable operational value, each built into existing systems rather than bolted alongside them.
Automate repetitive processes and the handoffs between them, from document intake and data entry through to routine reporting.
Assistants that answer product and policy questions from your own information around the clock, and route to a person when a question needs one.
Systems that generate, structure, and maintain product and marketing content at catalogue scale, in a consistent brand voice.
Prospect research, enrichment, qualification, and outreach, connected to the CRM and sales process you already run.
Most useful AI work does not match a packaged category. It starts with a process that is expensive, slow, or inconsistent, and the question is whether a system can carry part of it reliably enough to trust.
We assess the process first, identify where AI genuinely helps and where conventional software is the better answer, and build against your existing systems, data, and constraints. That includes the integration and ERP work required to make it operational rather than a proof of concept.
Discuss an AI ProjectEngagement Model
01
Map the process, the data behind it, and where AI is and is not the right tool.
02
Define scope, integration points, review steps, and how quality will be measured.
03
Build, connect to existing systems, and test against real business data.
04
Refine output quality, adoption, and the operating process after launch.
AI development work often involves genuine technical uncertainty, which can make it eligible for SR&ED tax credits. As SR&ED advisors, we can tell you where that applies before the work starts. Read about SR&ED eligibility
Next Step
Tell us what the process is and where it breaks down. We will tell you honestly whether AI is the right answer, and what it would take to build.
Discuss an AI Project