Technology & Platforms
Software, semiconductor and platform companies are operating in the most intense AI cycle of their history. The advantage goes to teams that can rewire product, engineering, DevSecOps and go-to-market around AI without losing operational discipline.
Hyperscalers and AI-native firms are racing on model and agent capability. Established software vendors are re-architecting product portfolios. Across geographies, the constraint is increasingly talent, governance and the operating model, not compute or model availability.
What is happening, by region.
Microsoft, Google, AWS, Salesforce, ServiceNow and Adobe are racing to embed agents across their enterprise stacks. Mid-cap SaaS vendors are differentiating through verticalized AI rather than general assistants.
What we see working inside Technology & Platforms.
AI-native product development
Help product and engineering teams ship AI features that actually change customer outcomes, with eval and observability from day one.
MLOps and AI infrastructure
Stand up the model, agent, vector and eval stacks that let AI run in production at enterprise SLAs.
AI in DevSecOps and SDLC
Move beyond copilots to org-wide AI workflows across spec, code, review, test, security and release.
Platform engineering with AI copilots
Self-service platforms augmented with AI agents that lower cognitive load and lift developer throughput.
SaaS AI feature integration
Integrate Copilot, Vertex AI, Bedrock and Azure AI into the product stack with governance and pricing models that scale.
GTM and customer success agents
Sales, marketing and CS workflows powered by agents grounded in the firm's content, accounts and signals.