Potloc Rebuilds Research Platform Using Agentic AI
The research firm has integrated automated workflows to handle a vast majority of its quantitative analysis tasks.
Updated on Oct. 26, 2026 in Artificial Intelligence
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Potloc has officially transitioned its quantitative research platform to operate primarily on agentic AI. The company now utilizes automated workflows and AI agents to manage 85% of its research tasks.
Why it matters
By deploying agentic AI, the company intends to significantly accelerate its research processes. This shift maintains human oversight and relies on verified human respondents to ensure data accuracy throughout the automated workflow.
The platform now conducts 85% of its quantitative research tasks through specialized AI agents and automated workflows. The company is actively working to transition the remaining operational tasks to this system by 2027.
The players
Potloc
An international research firm with offices in London, Paris, New York, and Montreal that specializes in quantitative data collection.
The details
Potloc operates offices across London, Paris, New York, and Montreal to support its quantitative research business. The system rebuild embeds AI-driven agents into every step of the research cycle while keeping human verification as a core component.
Timeline
Potloc announced the platform rebuild on October 26, 2026.
The remaining non-AI tasks are scheduled for automation in 2027.
The Tech Race
The transition to agentic AI platforms represents a shift away from traditional, manual data-processing methods in the research industry. Potloc is positioning itself to compete with evolving analytics firms by replacing legacy manual workflows with autonomous agents.
Clients using the platform can expect faster delivery times for quantitative research projects due to the increased automation of data workflows. The integration of AI agents aims to streamline the experience while keeping professional human oversight in place.
The takeaway
The move demonstrates how firms are increasingly offloading high-volume quantitative labor to automated agents to gain efficiency. Companies seeking similar results should focus on balancing this automation with necessary human oversight to ensure output quality.
What happens next
The company is slated to complete the full transition of its remaining non-AI research tasks to automated workflows in 2027.
Further reading
Learn more about the latest innovations in Artificial Intelligence.
Source note: This article includes information reported by Research Live.
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