Enterprise AI Agent Consulting
Our senior engineers embed with your team to architect, build, and deploy AI agents that handle real workloads with clear guardrails and handoff.
Most AI agent projects fail between prototype and production
- Agents work in notebooks but break under real traffic and edge cases
- No observability means failures are hard to explain or reproduce
- LLM costs climb faster than teams expected once agents reach production volume
- Internal teams lack the specialized expertise to build reliable multi-agent systems
- Months wasted iterating without a clear production readiness framework
How we solve this
We use a repeatable readiness checklist, proven infrastructure patterns, and a measured deployment playbook to close the gap between prototype and production.
Agent Architecture Design
Production-grade architecture tailored to your use case, scale requirements, and compliance constraints
Full Implementation
Working agents deployed to your infrastructure with proper error handling, retries, and fallback strategies
Observability Stack
Complete tracing, monitoring, and alerting so you can see exactly what every agent is doing in real-time
Cost Controls
Per-run budgets, model routing, and caching layers that prevent runaway LLM spend
Team Handoff
Documentation, runbooks, and knowledge transfer so your team can maintain and extend the agents independently
How it works
Discovery Call
Free 30-minute deep-dive into your requirements, constraints, and success criteria
Architecture Sprint
We design the agent system, define KPIs, and create a scoped SOW with fixed pricing
Build & Deploy
Our engineers build and deploy with a scoped rollout plan and regular progress updates
Monitor & Optimize
We monitor the first 2 weeks of production traffic and optimize based on real data
Frequently asked questions
What AI agent frameworks do you work with?
We work with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, custom Python/TypeScript agents, and any framework that makes LLM calls. We are framework-agnostic and choose the best tool for your use case.
How is this different from hiring an AI contractor?
Contractors build what you spec. We bring production expertise - observability, reliability engineering, cost optimization, and security hardening - that most teams discover they need only after things break in production. We also transfer knowledge so your team becomes self-sufficient.
How do you approach production rollout?
We define a rollout plan around your scope, risk tolerance, and dependencies. Some teams start with a narrow production slice quickly, while broader programs need more instrumentation, approvals, and validation before launch.
Do you sign NDAs and work under enterprise security policies?
Yes. We work under your NDA, comply with your security policies, and can operate within SOC 2, HIPAA, and other compliance frameworks. Our engineers use your approved tools and follow your access control procedures.
Ready to get started?
Book a consultation with a senior AI engineer. We will use the conversation to understand your requirements and suggest next steps.
Book Free AI Agent Consultation