Natural-language agent builder
Create reasoning agents and structured workflows in plain language, with reusable skills and SOPs.
Create reasoning agents and structured workflows in plain language, with reusable skills and SOPs.
Agents answer – and act – through approved connectors, APIs, and MCP, within configured access and action boundaries.
Specialist agents, from Magnus or other platforms, hand off work so every request reaches the best one.
Ground every task in indexed knowledge and the way your people, policies, and systems connect.
Retain relevant context across sessions and improve agent behavior through feedback and review.
Built-in approvals, escalations, and handovers keep people in control of what matters.
Prompt-injection protection, PII redaction, policy enforcement, and audit trails, on by default, with a kill switch for every agent.
Model routing, pooled credits, and usage limits match each task to the right model and keep spend predictable.
Together, Simpplr and Magnus expand what
the business can do with AI.
Create agents around the outcomes your teams need, with the flexibility to
shape, extend, and refine them as the work evolves.
Go from idea to agent with natural language
Choose how much autonomy the work requires
Ground agents in how your business operates
Test, refine, and deploy with confidence

Magnus grounds every agent in what your organization knows: indexed knowledge, how people, policies, and systems connect, and memory that improves with use.
Ground answers and actions in your knowledge
Understand how your organization connects
Remember what matters and improve over time
Keep context current and permission-aware

Magnus runs agent work across approved models, tools, and connected systems, and keeps it moving through interruptions, approvals, and handoffs.
Orchestrate across agents, models, and tools
Run every step with the right context attached
Act within the right permissions
Keep complex work running, with people in control

Give IT visibility and authority over access, policy, performance, and consumption, while teams build and manage agents independently.
Control who can build, deploy, and use AI
Set safeguards for agent interactions
See what’s happening, and intervene when needed
Keep AI spending predictable as adoption grows











