What is agentic AI?
Agentic AI is artificial intelligence that can plan, use tools, and take multi-step actions toward a goal. It combines large language models with your business data and integrations to complete real workflows.
Agentic AI and AI Agent Development FAQ
Practical answers on agentic AI, custom AI agents, and AI workflow automation for enterprise teams.
What does an AI agent development company do?
An AI agent development company designs, builds, and operates custom AI agents. Fig AI Systems builds agentic chat assistants, multi-agent orchestration, and retrieval over your data with vector databases.
How are AI agents different from chatbots?
A chatbot answers questions; an AI agent completes work. AI agents plan multi-step tasks, call tools and APIs, and check their own results.
What does a custom AI system solve for enterprise teams?
Custom AI systems automate repetitive workflows, improve decision quality, and reduce response times. We design around your process constraints.
How is a custom AI solution different from off-the-shelf AI tools?
Off-the-shelf tools are generic by design. Custom AI agents are built around your data, business rules, and compliance needs.
What business problems are the best fit for AI agents?
The strongest AI agent use cases are high-volume, repeatable processes with clear quality standards. Examples include customer service, document review, and quoting.
How much does AI agent development cost?
AI agent development cost depends on scope. A focused single-workflow pilot costs a small fraction of a multi-agent platform build. Main drivers are integration depth, data readiness, and governance. We scope a fixed pilot first so you can validate ROI.
How long does it take to build and deploy an AI agent?
Most AI agent projects start with a focused pilot in a few weeks. Production follows in phases.
How do you integrate AI agents into our existing systems?
We integrate AI agents through APIs and workflow handoffs. Your teams keep using core systems such as CRMs and ERPs.
How do you handle security and data governance?
Security and governance are built into architecture decisions from day one. We define access controls, data boundaries, and logging.
Can your AI agents support human-in-the-loop review?
Yes. We design review gates for sensitive decisions and quality assurance checkpoints.
How do you measure ROI for AI agents?
We define success metrics before build-out: time saved per workflow, throughput, and error rates.
Do you support scaling after the initial pilot?
Yes. After pilot validation, we harden architecture, monitoring, and operations for higher volume.
What is the first step to start an AI agent project?
Start with a workflow discovery call. We map your process, identify bottlenecks, and recommend a pilot scope.