Research across sources
Collect and compare information while retaining sources, assumptions, and evidence for review.
AI Agent Development for Controlled, Measurable Business Work
YAS builds custom AI agents that research, classify, prepare, route, and assist—inside defined tools, permissions, review rules, and business workflows.
CUSTOM AI AGENT DEVELOPMENT
Where an AI agent is genuinely useful
Operator assistance
Prepare a decision, response, or next action while keeping the accountable operator in control.
High-volume classification
Sort requests, documents, leads, products, or content through explicit categories and confidence rules.
Multi-step tool use
Let an agent perform bounded actions across approved systems with permissions, logs, and stop conditions.
Agent capabilities we implement
Research agents with retained citations
Support and sales copilot workflows
Document extraction and classification agents
Content operations and publishing assistants
Internal knowledge and retrieval systems
Tool-using agents with approval gates and audit trails
How a production agent is built
- 01Define the job
We specify the task, allowed inputs, expected output, tools, permissions, and the human who owns the result. - 02Build evaluation cases
Representative success, ambiguity, and failure examples become the acceptance standard before autonomy expands. - 03Add tools and guardrails
The agent receives only the integrations it needs, with structured outputs, limits, logs, and escalation paths. - 04Observe real operation
We measure accuracy, exceptions, time saved, and operator corrections instead of judging a polished demo.
Model-independent architecture
A useful agent should not depend on one model brand. We select models by task quality, latency, privacy, and cost, then place them behind a controlled application layer with retrieval, tools, evaluation, and human approval where needed.
Agent does not mean unlimited autonomy
We do not give a probabilistic model unrestricted access to business systems. Permissions are narrow, irreversible actions require explicit approval, and uncertain work is routed to a person with enough context to decide.
FAQ
What is the difference between an AI agent and a chatbot?
A chatbot mainly exchanges messages. An agent can work toward a bounded goal using approved information and tools, while following explicit permissions and stop conditions.
Can an agent connect to our CRM or internal software?
Yes, when the system offers a safe API or another controlled integration surface. Access is limited to the actions required by the workflow.
How do you test an AI agent?
We use representative evaluation cases, inspect tool calls and evidence, track failures and human corrections, and verify the complete workflow rather than a single model response.