Strategy that translates directly into a 30-day pilot, not a 12-month report.
In plain English.
We turn vague AI ambition into a sequenced, budgeted roadmap your board can fund and your team can ship. We start from your P&L, not from a model catalog, and work backward to the handful of use cases that actually move revenue, margin, or speed.
The output isn't a slide deck that ages in a drawer. It's a prioritized backlog, a first pilot scoped to ship in 30 days, and a clear view of the data, tooling, and team you'll need to scale. We map every recommendation to the stack you already run (Salesforce, HubSpot, Snowflake, Vercel) so nothing requires a rip-and-replace.
Because we engineer and market what we recommend, our roadmaps are grounded in what's buildable now versus what's a research bet. You leave knowing exactly what to do next, what it costs, and what it returns.
When you need this
- Your board or leadership team is asking 'what's our AI plan?' and you don't have a defensible answer.
- You've run a few disconnected experiments but have no prioritized roadmap tied to revenue.
- You're about to commit real budget and want a sequenced plan before you spend it.
- A competitor just shipped something AI-native and you need to respond with a strategy, not a panic.
The deliverables, plainly stated.
- AI opportunity map scored by revenue impact, feasibility, and time-to-value
- Prioritized 12-month roadmap with a fundable first pilot scoped to ship in 30 days
- Stack-aware build/buy/partner recommendations across Claude, OpenAI, AWS, and your existing tools
- Data-readiness and capability-gap assessment with a hiring/partnering plan
- Investment model with cost bands and expected return per initiative
- Executive-ready narrative and one working session to align leadership
Typical duration
3 to 4 weeks
Investment band
$$Moderate investment
We scope in bands, not fixed numbers. Final pricing follows a quick scoping call.
A process built for this service, not a generic playbook.
- 01
Discover the economics
We interview leadership and operators, audit your data and your stack (Snowflake, Salesforce, HubSpot), and pin down where AI can change unit economics.
- 02
Map and score use cases
We surface 8 to 15 candidate use cases and score each on revenue impact, feasibility, and effort, separating buildable-now from research bets.
- 03
Sequence the roadmap
We sequence initiatives into a 12-month plan, pick the first revenue-tied pilot, and define the data and tooling each phase needs.
- 04
Align and fund
We package the plan into an executive narrative with cost bands and ROI, then run a working session to lock alignment and unblock the first pilot.
Team composition
An AI strategy lead and a solutions architect, with a fractional data engineer and a growth strategist pulled in as the use-case mix demands.
Tools & frameworks
- Native Bridge opportunity-scoring framework
- Claude and OpenAI for capability benchmarking
- Snowflake / BigQuery for data-readiness review
- Salesforce and HubSpot stack mapping
What we tie this engagement to.
Every engagement carries a revenue-tied KPI. These are the outcomes this service typically anchors on.
A funded, board-approved 12-month AI roadmap
A first revenue-tied pilot scoped and ready to ship in 30 days
A clear build/buy/partner decision for every initiative
Works with your stack
We deliver AI Strategy & Roadmapping inside the tools you already run.
AI Strategy & Roadmapping: common questions
What is an AI strategy and roadmap engagement?
It's a 3 to 4 week engagement that produces a prioritized, budgeted 12-month AI roadmap tied to your P&L, plus a first pilot scoped to ship in 30 days. The output is a fundable plan and backlog, not a theoretical report.
How is this different from a typical AI strategy consulting project?
Most strategy projects end at a slide deck. Because Native Bridge also engineers and runs marketing, our roadmaps are grounded in what's buildable now on your existing stack (Salesforce, Snowflake, Vercel) and flow directly into a 30-day pilot rather than a 12-month study.
How long does an AI roadmap take to build?
Typically 3 to 4 weeks: about a week of discovery and stack audit, a week of use-case mapping and scoring, and one to two weeks to sequence the roadmap and build the executive investment narrative.
Do we need clean data before you can build a roadmap?
No. Data readiness is part of what we assess. We review your Snowflake or BigQuery footprint and existing CRM data, then the roadmap explicitly sequences any data foundation work the priority use cases require.
What does an AI roadmap cost?
It sits in our $$ band, a fixed-scope strategy engagement priced well below an enterprise consultancy's multi-month study, because we deliver in weeks and the deliverable is an executable plan, not a deck.
Often paired with this.
Ready to put AI Strategy & Roadmapping to work?
Tell us where you are and we'll tell you what's blocking revenue.