Research

AI is reshaping healthcare across core subsectors—medical imaging and diagnostics, clinical decision support, precision medicine, remote monitoring and telehealth, mental health applications, and workflow automation—improving diagnostic accuracy, personalizing treatment, and streamlining operations. Our research highlights durable growth drivers, compelling momentum, and investment opportunities.

This report maps the transition from pilot projects to scaled deployments in logistics, manufacturing, and healthcare. We break down the stack—perception, simulation, planning, foundation models for robotics—and benchmark integration timelines, uptime, and payback. Attention is given to data flywheels, fleet orchestration, and safety certification as gating factors. We compare modular vs. vertically integrated approaches and highlight where software margins accrue as hardware commoditizes. 

This report examines the shift from descriptive dashboards to closed-loop AI that plans, executes, and learns across marketing, sales, and customer success. We assess data readiness, actionability inside system-of-record tools, and governance for model-driven execution. Our vendor landscape compares copilots, automation platforms, and vertical specialists on pipeline quality lift, cycle-time reduction, and NRR impact. We highlight patterns behind proprietary interaction data, embedded workflows, and measurable revenue efficiency, and outline adoption playbooks for enterprises modernizing their GTM stack.

This report examines how AI is moving from point tools to platform capabilities across e-discovery, contract lifecycle management, research, and knowledge ops. We analyze adoption drivers, barriers, and the evolving vendor landscape from incumbents embedding AI to vertical-first startups. We outline where value pools are consolidating and the indicators of durable moats.

This report analyzes AI’s impact on content pipelines and live operations: generative tooling for assets and levels, dynamic NPCs, personalization, and economy tuning. We evaluate effects on production cost, release cadence, and player LTV, and compare middleware that slots into existing engines versus full-stack creation suites. We profile early adopters, quantify workflow savings, and map where value accrues across engines, tooling, and live-ops optimization.