01
Tool-Using Agents
Build agents that can interact with APIs, databases, search systems, business tools, and controlled actions through explicit tool boundaries.
Service 03
Reasoning
Tool Use
Retrieval
Orchestration
Human Control
AI Agent Development
Build agents
that can act
with control.
Nanexi engineers agentic AI systems that can reason through defined tasks, retrieve knowledge, use approved tools, interact with software, and progress through workflows with validation and human oversight.
Build an AI agentAgentic systems
Autonomy needs
architecture
around it.
An AI agent is more than a model generating text. It may need to choose tools, retrieve context, maintain workflow state, interact with systems, evaluate results, and decide what happens next.
Those capabilities introduce new failure modes. Nanexi designs agents around explicit tools, permissions, workflow boundaries, validation, observability, and human intervention where it matters.
Capabilities
From reasoning
to controlled
action.
Build agents around the actual work they need to perform, the tools they are allowed to use, and the boundaries they must respect.
02
Knowledge Agents
Connect agents with documents, internal knowledge, structured data, search, retrieval, and evidence needed to reason about domain-specific tasks.
03
Workflow Agents
Design agentic systems that operate inside multi-step workflows with business rules, state transitions, approvals, and deterministic boundaries.
04
Agent Orchestration
Coordinate reasoning, tools, sub-tasks, context, workflow state, retries, escalation paths, and multiple specialized components.
05
Agent Evaluation
Test tool selection, reasoning paths, grounding, task completion, failure behavior, permissions, consistency, and production reliability.
06
Agent Integration
Integrate agents into SaaS products, internal systems, APIs, business software, databases, cloud environments, and existing operational workflows.
Agent design
Don't give
the agent
unlimited
freedom.
Useful agentic systems need explicit tools, defined permissions, observable decisions, structured workflow state, validation, and clear escalation paths. Autonomy should expand only where the system can support it.
What we build
Agents designed
around specific
responsibilities.
The strongest agent systems begin with a defined responsibility, not a vague goal of making software more autonomous.
Research Agents
Agents that retrieve information, inspect multiple sources, organize findings, maintain evidence, and prepare structured research output.
Document Agents
Agents designed to work through document-heavy tasks including extraction, analysis, comparison, review, knowledge retrieval, and structured response workflows.
Operations Agents
Agentic systems that support recurring business operations by interpreting inputs, applying workflow rules, interacting with systems, and escalating when required.
Knowledge Agents
Agents grounded in internal knowledge that help users retrieve, understand, connect, and work with organization-specific information.
Product Agents
Agent capabilities embedded inside SaaS applications and software products to complete defined user tasks through tools and structured workflows.
Multi-Step Task Agents
Agents that break a defined objective into controlled steps, gather context, use approved tools, validate intermediate results, and progress toward completion.
Agent architecture
Five layers
behind a
reliable agent.
Reasoning is only one layer. Tools, knowledge, orchestration, and control determine how safely and reliably an agent can complete work.
01
Reasoning
Models, instructions, planning behavior, structured decisions, decomposition, and task-specific agent logic.
02
Tools
APIs, search, databases, business systems, functions, external services, and controlled actions available to the agent.
03
Knowledge
Retrieval, documents, structured information, business context, evidence, metadata, and relevant domain knowledge.
04
Orchestration
Workflow state, routing, retries, branching, sub-tasks, checkpoints, escalation, and coordination across the agent system.
05
Control
Permissions, validation, observability, approval states, safety boundaries, human review, and failure handling.
Decide
Reason about
the next step.
The agent interprets the current state, available context, instructions, tool descriptions, prior results, and workflow boundaries before deciding what should happen next.
Act
Use an
approved tool.
Actions happen through defined tools and APIs rather than unrestricted system access, creating clearer permissions, logging, validation, and operational boundaries.
Controlled autonomy
More autonomy
means more
control.
As an agent gains the ability to call tools and affect real systems, permissions, validation, observability, approval states, rate limits, rollback strategies, and escalation become part of the core architecture.
Explicit tool permissions
Human approval checkpoints
Structured validation
Action and decision logs
Failure and retry limits
Escalation paths
Access control
Production observability
Agent engineering
From task
definition to
production agent.
01
Define
Identify the task, user, tools, information, actions, business rules, boundaries, failure states, and expected outcome.
02
Design
Define the reasoning flow, tool interfaces, retrieval strategy, workflow state, permissions, escalation paths, and approval points.
03
Engineer
Build the agent, orchestration, tools, APIs, data layer, application integration, logging, validation, and user experience.
04
Evaluate
Test task completion, tool calls, grounding, permissions, consistency, latency, failure behavior, and production edge cases.
05
Operate
Deploy with observability, collect production evidence, inspect failures, refine tools and instructions, and evolve workflows carefully.
Agent principles
How we think
about agentic
systems.
01
Give agents explicit boundaries
02
Use tools for actions, not assumptions
03
Ground decisions in available knowledge
04
Keep important actions reviewable
05
Design clear failure and escalation paths
06
Evaluate behavior before expanding autonomy
Related services
Build the
system around
the agent.
01
AI Development
Design the models, retrieval, reasoning, evaluation, and intelligence architecture behind the agent.
02
AI Application Development
Embed agentic capabilities inside complete SaaS products, business applications, and user workflows.
03
AI Automation
Connect intelligent agents with repeatable business processes, systems, APIs, and operational workflows.
AI Agent Development
Build agents
for real
work.
Tell us the task, workflow, systems, knowledge, and actions your agent needs to work with. We can design the intelligence, tools, orchestration, and control architecture around it.