AI Module 01 AI ARCHITECTURE PLANNING
Blueprints Before Burn Rate
The expensive part of AI isn't the tokens. It's building the wrong thing, on the wrong model, wired to the wrong data, and finding out three months later. We start every AI engagement with architecture: what's worth automating, how the pieces fit together, what it will cost to run, and how you'll know it's working. You walk away with a plan your engineers can build and your CFO can read.
Where AI Earns Its Keep
Use-Case Triage
Not every process needs an LLM. Some need a better spreadsheet. We map your workflows, score the candidates on value, risk, and data readiness, and tell you honestly which ones are worth the effort. The shortlist is usually shorter than the hype suggests, and a lot more profitable.
Data & System Audits
Agents are only as good as what they can reach. We look at where your knowledge actually lives (docs, tickets, CRMs, that one shared drive nobody admits to using), how clean it is, and what it will take to make it safely available to a model.
Boring Decisions That Save You Money
Model & Vendor Selection
Frontier model, small model, open weights, or a fine-tune? Hosted API or your own cloud? Or a System One model like Jev for the high-volume labeling and routing calls, where a full generative model would be slow, expensive overkill? We benchmark the options against your real tasks, not leaderboard screenshots, and pick the cheapest setup that clears the quality bar.
Cost & Latency Modeling
We estimate tokens, calls, caching, and peak load before launch, so the monthly bill is a forecast instead of a surprise. If an approach only pencils out at demo scale, you'll hear it from us first.
Services Overview
- Model Benchmarks
- Build vs. Buy
- Cost Modeling
The Blueprint You Get
Every engagement ends with a written architecture: system diagrams, data flows, the agents and tools involved, an evaluation suite plan with real test cases, security and access boundaries, and a phased rollout that delivers something useful early. It's yours to build with us, with your own team, or with whoever you like. (We hope it's us.)
Services Overview
- Architecture Docs
- Eval Suites
- Governance
- Roadmaps
- webvolta plan --client you
- week 1: interviews, workflow mapping, data inventory
- week 2: use-case scoring, model benchmarks on your tasks
- week 3: architecture, cost model, eval plan, risks
- blueprint delivered. first build phase ready to start.
Measure twice, prompt once.
Contact us for more info!!
Frequently Asked QUESTIONS
Why plan the architecture before building anything?
Because most failed AI projects fail on decisions made in week one: the wrong use case, the wrong model, or data the model can't reach. A few weeks of planning is far cheaper than a few months of rebuilding.
Do you recommend specific AI vendors?
We recommend whatever fits your tasks, budget, and data rules. We work with Claude, OpenAI, Gemini, open-weight models, and cloud platforms like AWS Bedrock, and we benchmark them on your real work before picking.
What do we get at the end?
A written architecture with diagrams, a cost model, an evaluation plan with test cases, security and governance guidance, and a phased roadmap your team can execute.
Can you review an AI system we already built?
Yes. We run the same process as an architecture review: what's working, what's fragile, what it costs, and what to fix first.