Agentic AI Consulting
I help founders ship production-ready agentic AI systems. That means multi-agent orchestration that works under real load, LLM governance that keeps your legal team happy, and observability so you know exactly what your agents are doing — before your users do.
What you walk away with
- ✓Agentic architecture document with agent graph, tool registry, and failure modes
- ✓LangGraph or custom orchestration implementation with Temporal for durability
- ✓Safety and guardrails layer — prompt injection defences, output validation, escalation logic
- ✓Observability pipeline — traces, latency histograms, token cost dashboards
- ✓Production deployment with canary rollout and rollback procedure
- ✓Handoff documentation and 2-week post-launch support
Engagement model
01
Architecture Design
Discovery Sprint
2 weeks. I audit your current stack, define the agent graph, pick the orchestration layer, and write the architecture document. Fixed price.
02
Core Agent Build
Pilot
4–6 weeks. We build the highest-risk agent path first — the one that, if it fails, breaks everything. This is your proof-of-concept with real users.
03
Full System Delivery
Build
8–14 weeks. Complete agentic system — all agents, tools, guardrails, observability, and deployment pipeline. Timeline depends on scope.
04
Fractional Oversight
Scale
Optional. Monthly retainer for ongoing architecture guidance, performance tuning, and new agent development as your product evolves.
Recent case study
SentientOps Control Center
Cut incident response from 42 minutes to under 7.
Read the full case study →Free tools
Free tools for agentic ai consulting
AI Agent ROI Calculator
Estimate payback, monthly savings, LLM cost, and 36-month NPV before you commit to a build.
Agentic AI MVP Cost Estimator
Planned estimator for build, run, and team cost by scope and capability.
Agentic AI Readiness Scorecard
Planned readiness quiz across data, operations, governance, skills, and product surface.
Frequently asked questions
- What agentic AI frameworks do you work with?
- My primary stack is LangGraph for agent orchestration and Temporal for durable workflow execution. I also work with LangChain, custom orchestration, Vertex AI Agent Builder, and AWS Bedrock Agents depending on your infrastructure constraints. I choose the framework that fits your stack — not the one I happen to know best.
- How is an agentic AI consultant different from a machine learning engineer?
- A machine learning engineer builds and trains models. An agentic AI consultant designs the systems that use those models — the agent graphs, tool registries, orchestration layers, safety mechanisms, and production deployment architecture. I work with existing foundation models (GPT-4, Claude, Gemini) rather than training new ones.
- What does a typical agentic AI project cost?
- Discovery sprints start at $8,000–$15,000 for a 2-week architecture engagement. Full agentic AI builds typically run $40,000–$120,000 depending on the number of agents, integrations, and compliance requirements. Monthly fractional retainers start at $6,000/month. Book a strategy call for a tailored estimate.
- Can you work with our existing engineering team?
- Yes — and this is usually the best model. I embed with your team for the architecture and pilot phases, then progressively hand off ownership during the build phase. The goal is a team that can extend and maintain the system without me.
- Do you work with regulated industries?
- Yes. I have shipped agentic AI systems for fintech, DeFi, and institutional clients with SOC2 requirements and compliance constraints. Safety layers, audit trails, and governance frameworks are built in from the start — not bolted on at the end. See the SentientOps case study for a detailed example.
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Ready to start a Agentic AI Consulting engagement?
Book a 30-minute strategy call. I will map out a scope and timeline specific to your situation.