AI Strategy & Consulting
Cut through the noise with clear AI roadmaps, architecture planning, and use-case validation.
An honest read on the work
No marketing voice. A direct explanation of what the engagement actually covers and what it does not.
AI Strategy and Consulting is for teams trying to make sensible bets in a market full of demos. The pressure to "do AI" is high and the cost of doing the wrong AI is real — wasted quarters, abandoned models, vendor lock-in, and an engineering team frustrated by initiatives that go nowhere. This service exists to put a clear plan between the boardroom enthusiasm and the engineering backlog.
We work with leadership teams, product orgs, and investors to identify where AI actually moves a metric the business already cares about, and where it is a distraction. The engagement produces a roadmap, a target architecture, a build-versus-buy point of view for every component, and a budget envelope by quarter. It is opinionated. We will tell you which of your ideas to drop, which to fund, and what order to sequence them in so the early wins fund the harder bets.
The SoftUs difference is that the consulting team has shipped. Every consultant has run real production engagements, knows what fails in the last mile, and refuses to recommend an architecture they would not build themselves. We do not produce hundred-page slide decks. We produce a roadmap you could hand to a competent engineering lead and ship from, plus the decision logs that explain why each call was made.
We are also vendor-neutral. We have no kickbacks with cloud providers, model providers, or tooling vendors. Our recommendation reflects what fits your team, your data, and your timeline — not a partner discount we are chasing. Engagements run two to eight weeks depending on scope and end with a written roadmap, an architecture diagram, a sequenced backlog with effort estimates, and a steering plan for the next two quarters.
Four situations this service fits
If you recognize yourself in one of these, the engagement will move quickly. If not, we will tell you in week one.
Enterprise leadership starting an AI initiative
The board asked for an AI strategy. You need a clear plan that prioritizes use cases by ROI and feasibility, identifies the data and infra gaps, and gives engineering something to actually build against.
Startup founder validating an AI product idea
You have a hypothesis for an AI-native product. Before raising or hiring, you need an honest read on technical feasibility, defensibility, and the realistic cost to reach a usable MVP.
Engineering leader modernizing a legacy system
You inherited an aging stack and stakeholders are asking for AI features. You need a sequencing plan that lets you ship value without rewriting the platform in one go.
Investor or board doing technical diligence
You are evaluating a portfolio company or acquisition target with a heavy AI claim. You need a frank read on what is real, what is brittle, and what the next twelve months of engineering cost looks like.
Five phases, end to end
The same shape every engagement runs in. Scoped weekly, demoed weekly, with a written deliverable at the end of every phase.
- Phase 01
Discovery & Scoping
1 weekWe interview leadership, product, and engineering, audit the current state of data and infrastructure, and identify the existing initiatives and their status. The output is a working hypothesis on where AI moves a metric you already track.
- Stakeholder interview synthesis
- Current-state audit
- Working hypothesis on top opportunities
- Engagement plan and timeline
- Phase 02
Use-Case Discovery
1 to 2 weeksWe run focused workshops with each business unit, surface candidate use cases, score them on impact, feasibility, data readiness, and time to first value, and shortlist the ones worth deeper analysis.
- Long-list of candidate use cases
- Scoring rubric and applied scores
- Shortlist of three to five priorities
- Workshop synthesis document
- Phase 03
Feasibility & Architecture
1 to 2 weeksFor each shortlisted use case, we run a feasibility check — data, model approach, build-versus-buy, integration cost — and design the target architecture covering data, model serving, observability, and security.
- Feasibility memo per use case
- Target architecture diagram
- Build versus buy recommendations
- Estimated cost and effort per case
- Phase 04
Roadmap & ROI
1 weekWe sequence the shortlisted use cases into a quarterly roadmap, model the ROI of each, identify dependencies and risks, and define the org and skills needed to execute. The plan is opinionated and reviewed with leadership.
- Quarterly roadmap
- ROI model per use case
- Org and hiring plan
- Risk register
- Phase 05
Handoff & Steering
1 weekWe walk the roadmap through leadership and engineering, set up a steering cadence for the next two quarters, and remain on call for follow-up decisions as the team starts execution. The plan is a living document.
- Roadmap walkthrough sessions
- Steering cadence agreement
- Decision log template
- Sixty- and ninety-day check-in plan
Tangible artifacts, not slide decks
At handoff, you receive a working system plus the documentation, dashboards, and runbooks needed to operate it without us.
The full AI/ML stack, end to end
From data ingestion to model training to vector retrieval to evaluation, we work across the tools production AI teams actually rely on. Reliable, well understood, and easy to hand off.
Languages
Modeling & Analytics
LLM & GenAI
Data Warehouses & Pipelines
Cloud & MLOps
Visualization & Reporting
Three ways to work with us
Pick the shape that matches your stage. We will tell you honestly if a different model would serve you better.
AI Readiness Sprint
A two-week sprint that produces a readiness assessment, a prioritized opportunity list, and a high-level architecture for the top use case.
Leadership teams trying to decide whether to invest in AI this year and where to start.
Strategy & Roadmap
A four-to-six week engagement producing a full roadmap, ROI model, architecture, and hiring plan ready to brief the board and execute against.
Companies committing to a multi-quarter AI investment and needing an opinionated plan to execute.
Fractional AI Advisor
A monthly retainer pairing your leadership with a senior SoftUs advisor for steering reviews, decision support, and quarterly roadmap refresh.
Teams executing on an AI roadmap who want a senior outside perspective without a full hire.
What you will gain
Concrete outcomes from our engagement — measurable impact you can track from day one.
Clear roadmap for AI adoption within budget
Validated high-ROI use cases to avoid wasted spend
Defined technical architecture for future scalability
Who we build for
We work across industries where data, AI, and automation unlock real competitive advantage.
Enterprises starting AI initiatives
Startups validating new AI products
Companies modernizing legacy systems
Investors evaluating product feasibility
Case studies
Examples of how we deliver under real constraints — timelines, data quality, and production requirements.
AI Policy Compliance Checker
Enterprises needed to continuously ensure internal policies aligned with evolving regulations across multiple jurisdictions.
Built an AI system that scans and flags outdated or non-compliant clauses in company policies, with automated regulatory database updates and risk scoring.
Enterprise AI Dashboard for KPI Forecasting
C-level leaders lacked real-time predictive insight into key business metrics, relying on lagging indicators and manual reporting.
Delivered an AI forecasting dashboard that predicts sales, churn, and demand using multi-source data integration and a 12-month forecasting horizon.
The honest answers
Direct responses to what you would ask on a first scoping call. If your question is not here, send it on the contact form and we will answer in writing within a working day.
How long does a typical engagement take?
A readiness sprint is two weeks. A full strategy and roadmap engagement is four to six weeks. Fractional advisory runs monthly with no fixed end date and can flex with your roadmap.
Who owns the deliverables and IP?
You do. Roadmaps, architecture diagrams, decision logs, financial models, and synthesis documents belong to you and are delivered in editable formats. We retain only generic frameworks.
Do you sign NDAs?
Yes. We sign NDAs before any work starts and treat interview content, financials, and competitive context as confidential. Diligence engagements run under target-blind protocols when required.
Will you also build what you recommend?
Optionally. We are vendor-neutral and will recommend in-house build, external build, or buy depending on what fits. If you want us to deliver the build, our delivery teams can take it on under a separate SOW with no obligation.
What happens after the roadmap is delivered?
Most clients move into a steering cadence — biweekly or monthly check-ins — for the first two quarters of execution. You can also bring our engineering teams in for the execution itself or keep us purely on advisory.
How do you price?
Strategy engagements are flat-fee by phase. Fractional advisory is a monthly retainer. We share the full quote before the SOW and we do not bill hourly for strategy work.
Do you do investor or M&A diligence?
Yes. We have run technical diligence for both Series A through C and PE-stage acquisitions. The output is a written diligence memo with risk-rated findings and remediation cost estimates.
Can you start from a vague problem?
Yes — strategy engagements are designed for vague problems. The first week is structured interviews to surface the real questions behind the framing you came in with.
Adjacent work we do
Engagements that often run alongside this one.
Bring this work in-house, fast
A thirty-minute scope call gets you a written plan and a fixed quote. No slide decks, no follow-up cycle.
Have an AI idea, messy workflow, or product vision? Let's make it buildable.
Bring the problem. We'll help shape the product, define the architecture, and show the fastest path to a serious first version.
A practical first roadmap in the discovery call
Architecture, timeline, and delivery options in plain English
Security, scalability, and reliability discussed upfront
Model registry
softus-rag-v4.2
187ms
Latency
128k
Context
$0.004
Cost / req
Evaluation suite
Deploy pipeline
prod / canary 25% — healthy