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How a Custom AI Assistant Saves Thousands of Research Hours for Twelve

Picture of Tonic3 Tonic3 : Jan 29, 2026 9:38:22 AM

Design & UX Velocity & Scale Adoption & Engagement Agentic AI

How a Custom AI Assistant Saves Thousands of Research Hours for Twelve

The AI Research Assistant has become an indispensable tool. It completely changed how our R&D team accesses historical data, allowing them to focus their valuable time on innovation, not manual retrieval.

R&D Leadership @ Twelve

R&D staff in the manufacturing sector wasted valuable time manually searching historical experiment archives, hindering productivity and innovation speed.

Developed a custom Generative AI Research Assistant that uses Retrieval-Augmented Generation (RAG) to instantly access proprietary data.

Twelve immediately boosted Employee Productivity by significantly reducing time spent on manual data retrieval and accelerating research cycles.

Immediate

Access to Historical Data

Cut in Half

Manual Data Retrieval Time

Proprietary

Data Security (RAG Model)

Custom-Built

Integration with R&D Archives

The Challenge:

The Bottleneck of Manual Knowledge Retrieval in Manufacturing

Twelve’s R&D team, focused on advancing industrial innovation in manufacturing, faced a critical bottleneck: valuable research time was lost to manually searching immense archives of historical experiment data. This inefficiency directly impacted Employee Productivity and slowed the pace of innovation. The challenge required a secure, intelligent solution to transform knowledge retrieval.

Human-Centered UX: Accelerating Research Workflows

The design process was deeply Human-Centered. We mapped the researcher's workflow to build an intuitive, chat-based interface. The UX ensures that the R&D team can easily query, cross-reference, and receive suggested refinements to experiments, promoting adoption and ensuring the tool is an aid to—not a hurdle for—productivity.

AI Strategy: Generative AI for Instant Precision

We built a custom AI-Powered Research Assistant utilizing Retrieval-Augmented Generation (RAG). This solution ensures the AI delivers instant, precise answers by grounding its knowledge in Twelve's proprietary experiment archives, bypassing generic public knowledge and ensuring data security. This immediately freed up high-value R&D staff.

Custom-Built Code: Secure Integration and Scalability

We focused on robust, Custom-Built Code to securely integrate the GenAI model with Twelve’s internal data storage systems (e.g., historical archives). The engineering rigor ensured the solution was scalable, reliable, and maintained data governance standards essential for an R&D environment in advanced manufacturing.

The Impact: Strategic Performance & R&D Advantage

The AI Research Assistant achieved Intelligent Transformation by fundamentally changing Twelve’s R&D workflow. By automating the low-value task of data retrieval, the solution immediately boosted Employee Productivity, allowing researchers to dedicate their time to high-value experimentation and innovation.