AI without execution
The model suggests the next step, but a person still copies information and operates each system.
Autonomous AI agents for enterprise
AI agents that operate a complete workflow—with permissions, controls and human approval
An autonomous agent does more than answer a question. It receives a bounded goal, gathers context, selects from approved tools, updates ERP or CRM, verifies the result and escalates decisions outside its authority.
What the engagement creates
An autonomous-agent operating layer above existing systems
- Acts across existing ERP, CRM, documents and internal systems
- Limited to predefined tools, permissions and escalation rules
- Every action is logged, evaluated and available for human intervention
Public catalog prices for agents, multi-agent systems and integrations. View pricing
As featured in
Businesses already working with us
Sectors where we have delivered automation and AI-agent projects in Israel
The operating problem
The enterprise gap is between AI that explains and a system that acts
Organizations already know how to generate an AI answer. Greater value begins when an agent owns a bounded workflow and acts inside existing systems.
Access without boundaries
An agent with excessive access creates risk; an agent without tools remains a chat interface.
Pilots without evaluation
Without action logs, quality checks, exception queues and operating ownership, adoption cannot scale.
The system
An autonomous-agent operating layer above existing systems
Each agent receives a goal, context and bounded tools. It plans the next step, performs only approved actions, verifies the result and escalates exceptions with full context.
Understand state and goal
The agent reads an event, document or request, gathers approved context and defines the required result.
Plan and act through tools
The agent selects from bounded tools: search, calculation, document creation, system update or a specialist agent.
Verify, record and escalate
The result is checked against rules, written to the source of truth and logged; sensitive decisions require approval.
Enterprise research
Demand is rising faster than safe agent operations
The market has moved from whether to use agents to which workflow they should own, what authority they receive and how performance is evaluated. That is why enterprise work should begin with one bounded, controlled process.
81%
Agents are entering enterprise AI strategy
Leaders expect agents to be moderately or extensively integrated into their organization’s AI strategy within 12–18 months.
Microsoft Work Trend Index 2025<10%
Few enterprises have scaled tangible value
Although nearly two-thirds of enterprises have experimented with agents, fewer than one in ten have scaled them to tangible value.
McKinsey, April 202640%
Enterprise applications are moving to task agents
Gartner forecasts that up to 40% of enterprise applications will include task-specific agents by the end of 2026, up from under 5% in 2025.
Gartner forecast, August 2025Concrete scope
What an enterprise agent system includes
Goal, boundary and authority definition for each agent
Tool, permission and source-of-truth map
ERP, CRM, document and internal-system connections
Orchestrator and specialist agents where required
Pre-action test scenarios and quality measures
Approval, exception and human-handoff queues
Action logs, monitoring and alerts
Documentation, training and operating ownership
From the first agent to enterprise capability
The first workflow proves authority, tools, evaluation and handoff. The same controlled foundation can then serve more agents, workflows and teams.
Stage 1
Choose a bounded workflow and define authority
Define the goal, tools, information, allowed actions, prohibited actions and human approvals.
Stage 2
Run real scenarios and evaluate
Measure accuracy, action success, exceptions, completion time and whether escalation reaches the right owner.
Stage 3
Add agents and workflows on the same controls
Expand from tools, permissions, knowledge, evaluations and monitoring proven in the first workflow.
Examples of enterprise operating systems
Manufacturing
Priority, pricing, documents and production planning
A locally hosted operating layer across commercial, engineering and production information.
Read the caseProfessional services
CRM, telephony, enrichment and portals
One system for representatives, managers, clients and marketing data.
Read the caseDelivery management
Projects, tasks, knowledge and documents
A shared workspace for the full technical-project delivery journey.
Read the caseChoose one workflow an autonomous AI agent should operate for you
Send us a short description or voice note: what triggers the workflow, which systems it crosses and where it stalls. We will return with a practical direction.