AI Strategy & Roadmap
A technical roadmap that connects AI ambitions to engineering reality.
Overview
From AI Vision to Engineering Plan
You know AI belongs in your product, but the landscape moves fast and the options are overwhelming. We help you cut through the noise with a grounded, technical AI strategy — model selection, architecture decisions, build-vs-buy analysis, and a phased roadmap your engineering team can actually execute.
The Problem
Why AI Strategy Fails Without Technical Grounding
Most AI strategies are written at the whiteboard level and never survive contact with the codebase. The gap between "we should add AI" and a shipped feature is where most initiatives stall.
Shiny Object Syndrome
New models and frameworks launch weekly. Without a disciplined evaluation process, teams chase the latest release instead of building on stable foundations that serve their actual use cases.
Strategy-Execution Gap
High-level AI strategies rarely account for data readiness, infrastructure constraints, or team capabilities. The result is a roadmap that looks great in a slide deck but stalls in sprint planning.
Misallocated Investment
Building when you should buy, or buying when you should build, can cost months and hundreds of thousands of dollars. Getting the build-vs-buy decision right early is critical.
What We Deliver
A Roadmap Grounded in Technical Reality
Model & Architecture Selection
We evaluate your use cases against the current model landscape — LLMs, embedding models, fine-tuned vs. prompt-engineered approaches — and recommend architectures that balance capability, cost, and operational complexity.
Build vs. Buy Analysis
For each capability on your roadmap, we provide a clear recommendation: build in-house, integrate a managed service, or use an open-source solution. Every recommendation includes cost projections and trade-offs.
Phased Implementation Roadmap
A sequenced plan with milestones, dependencies, and decision gates. Each phase builds on the last, so you're shipping value incrementally — not betting everything on a single big-bang release.
Cost & Resource Modeling
Realistic projections for inference costs, infrastructure, and engineering time across each phase. You'll know what each initiative costs before you commit, from POC through production scale.
Data Readiness Assessment
We evaluate your existing data assets, pipelines, and quality to determine what's ready for AI workloads and what gaps need to be closed before you can execute on the roadmap.
Risk & Contingency Planning
Documented risks, fallback options, and go/no-go criteria for each initiative. If a model provider changes pricing or a capability doesn't meet quality thresholds, you have a plan B ready.
Who It's For
Is This Right for You?
AI Strategy & Roadmap is designed for product and engineering leaders who need a clear, actionable plan.
- You have multiple AI use cases competing for engineering bandwidth and need to prioritize
- You want a technical evaluation of build vs. buy options before committing budget
- You need cost projections and phased milestones to secure internal buy-in
- Your team is capable but needs guidance on model selection and architecture patterns
- You want to avoid costly rework by making the right architectural decisions upfront
Ready to build your AI roadmap? Contact us or email info@techsight.dev to schedule a consultation.