True cognitive
reasoning
Not just automation. Real intelligence that understands context, analyzes patterns, and makes decisions.
Our agents process information like humans do—considering multiple factors, weighing options, and choosing the best path forward.
Lightning fast
execution
Multi-agent
orchestration
Deploy teams of specialized agents that work together to solve complex problems
Customer Service
Data Analysis
Sales Automation
Learns and
improves
Every interaction makes your agents smarter. Patterns emerge. Performance optimizes automatically.
Build agents.
No code needed.
Visual builder with drag-and-drop simplicity. Deploy production-ready agents in minutes.
Real results.
Real impact.
Automate
your sales
Qualify leads, schedule meetings, send follow-ups. All automated.
Intelligent
data analysis
AI that finds insights humans miss. Automatic anomaly detection and predictive analytics.
Complex workflows.
Simple execution.
Chain multiple agents together. Handle complex multi-step processes automatically.
Connects with
everything
1,400+ pre-built integrations. Or build your own in minutes.
Calculate your
ROI
See how much you could save with AI automation
Real companies.
Real results.
Trusted by leaders
Autonomous Agents That Think, Plan, and Act
Agentic AI goes beyond chatbots and copilots. Our agents reason about complex goals, break them into actionable steps, select and use the right tools, learn from feedback, and collaborate with other agents — all while staying aligned with your business rules and compliance requirements.
Goal-Driven Reasoning
Agents don't just follow scripts — they understand objectives. Given a high-level goal like "resolve this customer's billing issue," an agent decomposes it into steps, gathers context from your CRM and billing system, decides what action to take, and executes it — adapting when it encounters unexpected situations.
Key Use Cases
- Handle complex multi-system customer requests
- Automate research and analysis tasks
- Execute business logic that spans multiple tools
Multi-Step Planning & Execution
Agents create execution plans, sequence tool calls, manage dependencies between steps, and recover from failures mid-workflow. If a step fails, the agent retries with adjusted parameters, falls back to an alternative approach, or escalates to a human — all without losing context or state.
Key Use Cases
- Orchestrate workflows across 10+ systems
- Handle approvals and exception routing
- Recover gracefully from API failures and timeouts
Multi-Agent Collaboration
Deploy specialized agents that work together on complex tasks. A coordinator agent breaks work into sub-tasks, assigns them to specialist agents (billing expert, support agent, data analyst), aggregates results, and synthesizes a final answer. Agents communicate via structured protocols and share context efficiently.
Key Use Cases
- Build a virtual team of AI specialists
- Handle diverse expertise in one workflow
- Parallelize work across multiple agents
Tool Use & Function Calling
Agents dynamically select and call the right tools for each step — APIs, databases, code execution, web search, or other agents. The platform handles function calling, parameter extraction, result parsing, and error handling. Agents learn which tools work best for which tasks over time.
Key Use Cases
- Query databases and APIs with natural language
- Execute code and analyze results
- Search the web for real-time information
Memory & Context Management
Agents maintain context across long conversations and multi-day workflows. Short-term memory tracks the current task, while long-term memory stores preferences, learned patterns, and entity relationships. Context windows are managed automatically to prevent token overflow and reduce costs.
Key Use Cases
- Remember customer history across interactions
- Maintain state in multi-day workflows
- Reduce redundant API calls with caching
Guardrails & Human Oversight
Every agent runs within configurable guardrails — allowed actions, data access scopes, approval requirements for sensitive operations, and automatic escalation rules. Human-in-the-loop checkpoints let you review and approve before agents take consequential actions like sending payments or modifying production data.
Key Use Cases
- Require human approval for high-stakes actions
- Restrict agents to read-only on sensitive systems
- Audit every decision with full traceability
Each capability is production-ready, enterprise-tested, and integrates seamlessly with your existing toolchain. Deploy individual features or the full suite — your AI transformation scales with your needs.
Frequently Asked Questions
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Cloud Platform
Scalable cloud infrastructure for enterprise AI deployment. Multi-region, auto-scaling, and enterprise-grade security.
Developer Tools & SDK
Build custom AI agents with our comprehensive SDK, CLI tools, and developer APIs. Full documentation and code examples.
ROI & Savings Calculator
Calculate your ROI and savings from implementing Agentic AI automation. See productivity gains and cost reduction.
Documentation
Complete documentation for building, deploying, and managing AI agents. Installation guides, tutorials, and best practices.
API Reference
Full API reference for the 1C Platform. Endpoints, authentication, and code examples in multiple languages.
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In-depth articles on agentic AI, generative AI, AI governance, architecture, design, and enterprise adoption.
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