Certara adds NVIDIA’s BioNeMo Agent Toolkit to its drug‑development platform

What changed: Certara announced it has integrated NVIDIA’s BioNeMo Agent Toolkit into its biosimulation and evidence platform, making agentic workflows an option for tasks such as dosing optimization, clinical‑dataset interrogation, trial scenario simulation and regulatory evidence assembly.

Why it matters: Life‑sciences teams can now run AI agents that reason over validated models and datasets rather than only drafting text — that lets scientific teams speed hypothesis testing and produce reproducible analyses that are easier to map into regulator‑facing packages. For founders and biotech operators, this is a practical path to embed agentic automation into R&D workflows while keeping scientists in the loop.

Try/watch: If you run preclinical or translational programs, talk to your Certara contact about a pilot focused on a single decision point (dose selection or interim analysis) to measure time saved and auditability risk.

Automox MCP Server 2.2: visual review and “agentic” patch policies for endpoints

What changed: Automox released MCP Server 2.2, which adds a visual review surface for AI actions, a Patch‑by‑Severity policy builder, and a live capability discovery feature so agents can see what tools and credentials are available before acting.

Why it matters: For IT and security teams, this update turns agentic endpoint management from a black box into a human‑reviewable process — you get pause/approve surfaces and a way to scope agent actions by severity, reducing accidental mass changes and runaway automation costs. Operators can safely pilot autonomous remediation across a subset of machines rather than trusting fully automatic runs.

Try/watch: Pilot MCP 2.2 on a small fleet with the visual review enabled and test rollback procedures; measure false positives/negatives and how often agents request elevated actions.

Airia adds inline budgeting and spend attribution for agentic AI

What changed: Airia rolled out Enhanced Cost Optimization that enforces budgets and provides granular attribution for AI spend across providers, models, teams, agents and individual executions so organizations can block or throttle runs that exceed policy.

Why it matters: As agents multiply, consumption-based surprises become a primary operational risk; this feature gives finance, procurement and platform teams the controls to stop runaway agents before invoices arrive and to trace which agent, workflow, or model caused the spend. Buyers and consultants should treat this as a prerequisite control when deploying multi‑model or multi‑tenant agents.

Try/watch: Add Airia’s budgeting hooks to any agent pilot that calls external models or tools; require cost alerts and hard limits for non‑production agents.

Featured launches an MCP server so PR teams can run agents on their own accounts

What changed: Featured (an AI co‑pilot for PR) made its Model Context Protocol (MCP) server generally available, letting MCP‑compatible agents (Claude, Cursor, VS Code and others) act inside a user’s own Featured account — not via a shared API key. (MCP here means a local service that gives an agent scoped access to a product account.)

Why it matters: For small agencies and solo founders, that reduces the security and multi‑tenant risk of handing an agent a global API key — agents operate within the user’s account and available templates/workflows, which simplifies auditing and access control and makes agent automation practical for routine outreach and media monitoring.

Try/watch: If you run a PR or comms shop, test the MCP server with non‑sensitive tasks first (media searches, draft lists) to validate permission scoping and remove write access until you’re comfortable with the agent’s behavior.