Transforming expert consulting with AI automation

InnovMarine accelerates complex qualification work with AI driven automation built with IBM watsonx

Cargo ship on the water
High complexity intake with scarce expertise

InnovMarine delivers trusted digital solutions to the marine and defense industry, enhancing information flow and standardizing workflows across design, construction and maintenance of assets. InnovMarine’s experts must conduct multiple interviews while delivering consulting services, gather detailed information and guide each client through a highly structured intake. With only a small number of specialists able to perform this work, the team could support just two or three companies per week. As demand grew, this expert‑dependent workload placed increasing pressure on capacity, limiting scalability and slowing how quickly applicants could move forward.

4–10× increase in weekly capacity ~50–70% cost reduction
Innovation is most impactful when it solves real business challenges. Our collaboration with IBM allowed us to accelerate the development of innovative AI-driven solutions while staying focused on delivering greater value, faster and more consistently for our clients. This initiative demonstrated how human expertise and advanced technology can work together to transform complex business processes and create new opportunities for growth.
Pierre-Charles Drapeau President InnovMarine
Automating expertise heavy qualification work

To address growing demand for qualification support, InnovMarine collaborated with IBM to modernize its expert‑dependent intake workflow using IBM® watsonx® Orchestrate®. Working closely with IBM Technology Expert Labs®, the team captured the organization’s deep domain specific knowledge and structured it within a governed AI model capable of guiding applicants through a highly detailed process.

The virtual assistant supports intake from the first interaction, gathering information, organizing documentation and generating reports, emails and task requests automatically—activities that previously required extensive human involvement. By automating repeatable steps while preserving SME oversight for sensitive decisions, InnovMarine created a more scalable operating model. The new digital workflow reduces bottlenecks, shortens turnaround times and improves consistency for organizations navigating complex qualification programs. IBM Technology Expert Labs supported the implementation, helping ensure operational readiness.

Charting more impact from expert insight

By rethinking how specialized qualification and intake work is executed, InnovMarine gained the ability to scale a once‑constrained, expert‑driven process. Automation now handles the structured steps—capturing information, assembling documentation and generating formal outputs—so human specialists can focus exclusively on the judgment and interpretation that deliver value. As a result, InnovMarine can support significantly more qualification initiatives without increasing team size, accelerating time to engagement while improving consistency and predictability.

This shift also reduced the cost of guided qualification support, lowering the barrier for organizations seeking to participate in high‑value qualification programs. The new model has become a recognized differentiator for InnovMarine, drawing strong interest at defense and industry forums and prompting international inquiries about how similar AI‑enabled frameworks could modernize complex evaluation processes in other markets.

About InnovMarine

InnovMarine, based in Lévis, Quebec, provides trusted digital solutions to the marine and defense industry. The company integrates toolsets and optimizes workflows to improve information flow, enhance standardization and boost efficiency across the asset lifecycle—helping teams design faster, build better and maintain smarter.

Solution components IBM® watsonx Orchestrate® IBM watsonx® IBM Technology Expert Labs®
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Examples presented as illustrative only. Actual results will vary based on client configurations and conditions and, therefore, generally expected results cannot be provided.