What We Build With It
Agents focused on specific, high-value tasks with clear outcomes.
Research and Intelligence Agents
Monitor sources and produce structured briefings.
Document Processing Agents
Extract and validate data from high-volume documents.
Support Triage and Routing
Classify and route requests with context summaries.
Scheduling and Coordination
Handle routine coordination without back-and-forth.
Data Reconciliation
Compare records across systems and flag discrepancies.
Report Generation
Assemble scheduled reports from multiple sources.
Why Our Approach Works
Reliability comes from constraints and guardrails.
Narrow Scope, High Reliability
Agents do one thing well instead of many things poorly.
Predictable Frameworks
Validation gates and structured outputs keep behavior stable.
Escalation by Design
Agents know when to hand off to a human with full context.
Our Approach to Intelligent Agents
Production agents built with real software engineering discipline.
Orchestration
State management and tool use without fragile glue code.
Model Selection
Right-sized models for each task and cost profile.
Scheduling and Triggers
Event and time-based execution with retries.
Tool Integration
Secure connections to the systems agents must use.
Observability
Logs and traces that explain every decision.
Memory and State
Persistent context without creating hidden risk.
Frequently Asked Questions
What is the difference between an agent and a chatbot?
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Agents take actions across systems. Chatbots respond in a conversation. The extra power requires stricter controls.
Can we trust an agent without human oversight?
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For low-risk tasks, yes. For anything irreversible or high stakes, we add approval gates.
What happens when an agent gets stuck?
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We set confidence thresholds and escalation paths so failures are loud and recoverable.
How do you protect against prompt injection?
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We sanitize inputs, constrain permissions, validate outputs, and log actions for auditability.
When do multi-agent systems make sense?
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When the workflow naturally splits into roles. We start simple and add complexity only when it pays off.