What we build and how we help.
OPZET offers six service areas. Each can work as a standalone engagement or as part of a larger AI initiative.
Not sure where to start? Most new clients begin with Discovery and Assessment: a short review of your situation that tells you what to build, buy, or skip before any development begins.
01
Strategy and Advisory
Who it's for: Organizations that know they need to do something with AI but aren't sure where to start, what to prioritize, or what to build first.
What's included:
- AI Readiness Assessment and Audit
- AI Strategy and Roadmap Development
- Fractional AI Lead / Advisor (ongoing)
- Vendor and Tool Evaluation
- Executive Briefings and Workshops
What you get:
A written assessment or roadmap with prioritized recommendations. Not a slide deck full of frameworks. Specific, actionable guidance on what to build, what to buy, what to skip, and in what order.
How we approach it:
Most AI roadmaps fail at the prioritization step. We start with the constraint, not the opportunity.
Typical engagement:
1–3 weeks for a discovery and assessment. Ongoing advisory available on a monthly retainer.
02
Custom AI Development
Who it's for: Organizations ready to build a specific AI system and needing the technical expertise to get it done properly.
What's included:
- LLM Integration and Prompt Engineering
- Retrieval-Augmented Generation (RAG) Systems
- AI Agent Design and Development
- Model Fine-Tuning and Evaluation
- Custom AI Application Development
What you get:
A production-ready AI system built to defined acceptance criteria. Not a prototype that requires six more months of internal work before it can be used.
How we approach it:
A proof of concept that requires six more months of internal work before anyone can use it is not a proof of concept. We build to defined acceptance criteria and do not hand off work that is not production-ready.
Typical engagement:
2 weeks (POC) to 16 weeks (full build), depending on scope.
03
Workflow Automation
Who it's for: Organizations with manual, repetitive processes that AI can take over or meaningfully accelerate.
What's included:
- AI Workflow Design and Architecture
- No-code and Low-code Automation Builds
- Custom Code Automation
- Integration with Existing Systems (CRM, ERP, internal tools)
What you get:
A documented automation that runs reliably, integrates with the tools your team already uses, and reduces the manual overhead it was designed to eliminate.
How we approach it:
Automation that your team does not trust will not get used. We design for adoption from the start, which means involving the people who will use the system before we build it.
Typical engagement:
2–8 weeks depending on complexity and integration depth.
04
Data and Infrastructure
Who it's for: Organizations whose AI ambitions are blocked by data quality, data access, or a lack of the infrastructure that AI systems require.
What's included:
- Data Preparation and Pipeline Design
- Data Cleaning and Annotation Oversight
- Vector Database Setup and Configuration
- Cloud Infrastructure for AI Workloads
What you get:
A data environment AI systems can use: clean, structured, accessible, and maintained.
How we approach it:
Most AI projects that fail do not fail because of the model. They fail because the data was not ready. We assess data quality before scoping any development work.
Typical engagement:
Scoped per project. Often included as a phase within a larger development engagement.
05
Training and Enablement
Who it's for: Organizations investing in AI tools who need their teams to understand, use, and trust those tools.
What's included:
- Team AI Literacy Workshops (half-day and full-day)
- Custom Training Program Development
- Ongoing Coaching and Q&A Sessions
- Documentation and Knowledge Transfer
What you get:
A team that is equipped to use AI systems well. Not handed a tool with no context.
How we approach it:
Handing a team a new tool with no context is how you get shelfware. Adoption is a design problem, not a training problem, and we treat it that way.
Typical engagement:
Half-day to full-day workshop, or ongoing monthly coaching sessions.
06
AI Adoption and Usability Research
Who it's for: Organizations adding AI to their business who need to know whether their people will use it, and what is standing in the way.
What's included:
- AI Interaction Audit
- AI Change Readiness Assessment
- AI Adoption Research Study
- AI Adoption Monitoring (retainer)
What you get:
Evidence-based findings on how your employees or customers experience AI systems: where trust breaks down, where adoption stalls, and what needs to change before those patterns become embedded habits.
How we approach it:
Most AI adoption problems get diagnosed after they show up in usage numbers. We research them before deployment and monitor them after, so you are not rebuilding trust in a system people have already learned to route around.
Typical engagement:
1–2 weeks for an audit or assessment. 2–4 weeks for a full research study. Ongoing adoption monitoring available as a monthly retainer.
Not sure which service fits your situation?
Most engagements start with a conversation about the problem, not a service menu. Tell us what you're trying to solve and we'll tell you honestly whether we can help.
Book a Discovery Call