Services
Three focused offerings for teams ready to run AI in production — not experiment with it.
We design and implement AI systems that integrate into real operations, survive edge cases, and remain maintainable after handoff. If you're looking for demos, slide decks, or speculative prototypes, we're not a fit.
1. Agent Ops Starter
What it is
A production-grade internal AI agent system designed to operate reliably inside your organization — with tools, memory, evaluations, and hard guardrails.
This is not a chatbot.
This is an operational system.
What's included
Agent architecture design grounded in real use cases
Tool and function calling integrated into your stack
Memory and context management (explicit, inspectable)
Evaluation harnesses and failure-mode testing
Guardrails, constraints, and safety controls
Deployment, monitoring, and documentation for handoff
Typical timeline
3–4 weeks from kickoff to production deployment.
Who it's for
Teams with a clear internal use case who need an agent that works reliably in production — not a demo for stakeholders.
Not a fit if
You're exploring ideas, testing prompts, or want a public-facing novelty experience.
2. Automation Pipeline Sprint
What it is
A short, intensive build to replace repetitive operational workflows with monitored, end-to-end AI automation.
We don't automate guesses.
We automate patterns.
What's included
Workflow audit and bottleneck identification
Pipeline architecture and transformation logic
AI model integration where it adds leverage
Error handling, retries, and observability
Monitoring, alerting, and runbooks
Integration with your existing tools and systems
Typical timeline
2–3 weeks from audit to live automation.
Who it's for
Operations or product teams spending significant time on repeatable, rule-based tasks that are already well understood.
Not a fit if
Your workflow is undefined, constantly changing, or still being discovered.
3. AI Product Launch Pack
What it is
A full-stack implementation to take an AI-powered product from concept to a deployed, production-ready MVP.
This is for validation with real users — not pitch-only prototypes.
What's included
Product scoping and technical architecture
AI model integration and prompt/system design
Frontend and backend implementation
Authentication, data handling, and infrastructure
Monitoring, logging, and error tracking
Codebase documentation and structured handoff
Typical timeline
4–6 weeks from concept to deployed MVP.
Who it's for
Founders and teams who need to validate an AI product with real users quickly, without cutting corners that create long-term debt.
Not a fit if
You're still exploring ideas or looking for mockups without real deployment.
Ready to start?
If you have a defined problem and want an AI system that actually runs, let's talk.
Book a 30-min callInitial calls are exploratory and do not constitute a service agreement.