Most teams start with Claude as an individual chat tool, so results depend on who writes the prompt and stay outside the systems where work happens. SoftServe maps the recurring work of your analysts, product managers, operations and finance teams and builds a shared knowledge base and workflows: Claude Skills and plugins that carry your team’s own methods, connected through MCP to Microsoft 365, Jira, Confluence or your CRM, within your admin controls. We train the team on these workflows, and each one is timed before and after, so leadership sees the gain per task.

R&D teams in life sciences, chemicals, materials and energy spend a lot of time on literature review, data preparation and documentation, with knowledge split across ELNs, LIMS and file shares. SoftServe embeds with the team and connects Claude and Claude Science to these sources, building agentic workflows for evidence synthesis, experiment planning and reporting, with Claude Code writing and running analysis and simulation code. Scientists own hypotheses, design and conclusions, and every output traces to its source data. Research cycles shorten without losing rigor.

Physical AI products run on firmware, robotics software and simulation code that only count as done once they work on real machines, and coding assistants can’t observe the hardware. SoftServe applies its agentic engineering methodology to these teams. With a pilot team, we build a context layer from datasheets, hardware specs and robot interfaces and connect Claude Code to embedded toolchains, test benches and simulators, so agents write code, run it on the target and fix defects from runtime feedback. Engineers learn the workflow on their own backlog and keep control of acceptance.