From $5,000/project
AI Agent Systems
For workflows too complex for simple automation.
When your process has branches, decisions, and exceptions that need judgment, a linear automation breaks down. I build multi-agent systems where specialized AI agents handle different parts of a complex workflow, coordinating with each other like a well-run team.
Example system flow
Example: Automated compliance review for a financial advisory firm
- 0101
New client document uploaded to the
firm's portal.
- 0202
Intake agent classifies the document type
(KYC, investment policy statement, account transfer).
- 0303
Extraction agent pulls key data points
client name, SSN, account numbers, risk tolerance.
- 0404
Validation agent cross-references against existin…
Validation agent cross-references against existing records and flags mismatches.
Connected systems
8
Example stages
6
Delivery model
Client-owned or managed
Optional managed server
Managed AI agent infrastructure
If your team does not want to run the agent service, I can operate it on isolated managed infrastructure with the agreed models, tools, approval paths, and observability. The recurring scope distinguishes infrastructure operations from new workflow development.
Managed server pricing
Quoted monthly
Model/API usage and connected vendor costs are separate. Human review, uptime, support windows, retention, and regulated-data controls are defined in the managed-service agreement.
What gets built, and when it makes sense
When you need agents vs. simple automation
Deterministic workflow automation is usually the better choice when rules, branches, validations, and recovery paths can be specified in advance. Agentic steps become useful when the system must interpret variable unstructured input or select among approved tools at runtime. Many production systems use both: deterministic code for control and an agent only where contextual interpretation adds enough value to justify its additional failure modes.
How my agent systems work
Each agent has a narrow role and a limited tool set. The system records handoffs, validates deterministic outputs where possible, and routes low-confidence or high-risk decisions to a person. The automation boundary and escalation rate are established with representative test cases; I do not promise a universal autonomy percentage before measuring the actual workflow.
Example: Automated compliance review for a financial advisory firm
End-to-end walkthrough
- 0101
New client document uploaded to the
firm's portal.
- 0202
Intake agent classifies the document type
(KYC, investment policy statement, account transfer).
- 0303
Extraction agent pulls key data points
client name, SSN, account numbers, risk tolerance.
- 0404
Validation agent cross-references against existin…
Validation agent cross-references against existing records and flags mismatches.
- 0505
Review agent compares the extracted data
with a version-controlled checklist approved by the firm's compliance team.
- 0606
A qualified reviewer approves filing and
notification. Flagged cases arrive with the source data and specific issues attached.
Integrations
Explore related work
See where this service fits, how it has been applied, and the technical work behind it.
Case studies
Use cases
Articles
Ongoing maintenance available at $500/month
Every project starts with a free call. If automation isn't the right fit, I'll tell you.