AI agents that act inside your workflows, with people in control.
Sails Software designs, builds and governs agents that read information, decide and act, and hand the decisions that matter to your people.
Governed AI, in production.
faster development
Closing the AI-to-production gap with governed AI delivery
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profit growth
AI-powered credit management
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user satisfaction
AI-driven laboratory analytics in real time
Read the case studyFrom first use case to agents in production.
AI strategy
We find the use cases where agents add the most value, check data and process readiness, and set how far each agent may act on its own.
Custom agent design
We define what each agent decides, the data it needs and when it escalates, then build single agents or teams of agents that work together.
System architecture
Agents get memory, monitoring and connections to your systems through APIs and data pipelines.
Governance and tuning
Role-based access, a log of every action, performance monitoring and regular reviews keep agents safe, compliant and accurate.
Enterprise rollout
Agents go live in phases, with user training, incident handling and documentation, and scale out under the same controls.
Six kinds of agents, matched to the job.
Each architecture fits a different kind of business problem.
Reactive agents
For high-volume, time-sensitive work with known patterns, such as routing customer inquiries by topic and urgency.
Deliberative agents
They plan before acting by modeling options and outcomes, such as a supply chain agent weighing cost, lead time, supplier reliability and risk.
Collaborative multi-agent systems
Specialized agents that coordinate and hand work to each other, orchestrated with frameworks such as LangGraph and AutoGen.
Generative agents
Built on large language models, they break a goal into tasks, call other systems and gather current data before acting.
Learning agents
They test strategies, measure results and adjust, such as a pricing agent that tries offers and tracks conversion.
Hybrid agents
Combinations of the types above in one coordinated system, for workflows that need several kinds of decision.
What is agentic AI?
Agentic AI uses software agents that perceive information, decide and act inside business systems, and escalate to a person when a decision needs human judgment. Sails Software builds agents with clear decision limits, an audit trail for every action and human sign-off where risk calls for it.
- Builds
- Single agents and multi-agent systems
- Frameworks
- LangGraph, AutoGen
- Controls
- Escalation rules, role-based access, action logs
- Rollout
- Phased, with user training
Frequently asked questions.
What is agentic AI?
Agentic AI uses software agents that perceive information, decide and act inside business systems on their own, and hand a decision to a person when it needs human judgment. Traditional AI answers or predicts; an agent completes steps in a workflow.
What kinds of agents does Sails Software build?
Reactive agents for high-volume routing, deliberative agents that plan before acting, collaborative multi-agent systems, generative agents built on large language models, learning agents that improve through reinforcement learning, and hybrids of these.
How does agentic AI improve operations?
It takes routine decisions and hand-offs out of queues, removes waiting time between steps and keeps work moving around the clock, while exceptions go to the right person.
Can agents work with our existing systems?
Yes. Agents connect to your applications through APIs and data pipelines and work alongside your teams rather than replacing your core systems.
How do you keep agents safe and under control?
Each agent has defined decision limits and escalation rules, role-based access, a log of every action, performance monitoring and human sign-off where the risk calls for it.
How does a Sails Software agentic AI engagement run?
We assess where agents add value, design the agent and its architecture, build and test it, roll it out in phases and keep optimizing it against the outcomes agreed at the start.
Start with an AI readiness assessment.
Tell us which workflow you want to fix first. We'll check the data, the risks and the path to production.