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95% of GenAI Projects Deliver Zero Return. The Cause Is the Data Layer, Not the Model.

MIT's 2025 research found 95% of enterprise GenAI pilots deliver no measurable return, and RAND puts AI project failure above 80%. The bottleneck is almost never the model. It's whether your data, architecture, and governance are ready. AI Readiness scores exactly that with our 100 Point Check, then ships a working prototype where you're ready, so you know whether to build now, fix the gaps first, or wait.

Schedule Consultation View Process
100-Point
Readiness Check methodology
2 weeks
To your first blueprint
3 tiers
Assessment, Prototype, Custom
From $25K
Fixed-fee engagements
Overview

What is AI Readiness & Prototype?

Most enterprise AI initiatives fail before the model is ever the problem. The data isn't structured for it, the architecture can't support it, governance isn't in place, or the use case was never viable. AI Readiness answers the question every leader is actually asking before committing budget: are we ready, and if not, exactly what has to change? We run the Spartera 100 Point Check, a weighted diagnostic across your data, use case, security, management, and team, and pair it with a vendor-neutral architecture review. Where you're ready, we build a working prototype on your real data so readiness is proven, not assumed. You leave with an evidence-based go, fix, or wait recommendation, a prioritized remediation roadmap, and, at the Prototype tier and above, a functioning proof of concept.

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The Spartera 100 Point Check, a weighted readiness scorecard across data, use case, security, management, and team

Vendor-neutral architecture blueprint with no platform lock-in

A working prototype on your real data at the Prototype tier and above

A clear, evidence-based go, fix, or wait recommendation

Three fixed-fee tiers: Assessment, Prototype, and Custom

The Challenge

Why Start With Readiness

The fastest way to waste an AI budget is to build on a data layer that was never ready. Readiness is the cheapest insurance you can buy.

The data layer is the real bottleneck

MIT 2025 found 95% of GenAI pilots deliver zero return. RAND puts AI project failure above 80%, twice the rate of non-AI IT projects. S&P Global reports 42% of companies abandoned most AI initiatives in 2025, up from 17% a year earlier. The common cause is data quality and architecture, not the model.

A score, not a hunch

The 100 Point Check turns readiness into a weighted, defensible number across five dimensions, so the decision to build, fix, or wait is grounded in evidence you can take to a board.

Prove it with a prototype

At the Prototype tier and above, we build a working proof of concept on your actual data. Readiness stops being a slide and becomes something you can see running.

Vendor-neutral by design

The architecture blueprint is platform-agnostic. We recommend what fits your stack and goals, not what we're paid to resell, so you avoid lock-in before you've even started.

Choose Your Starting Point

Two Ways to Run the Assessment

Same 100 Point Check, same two weeks, same fixed fee — scoped to where you are in your AI journey.

Discover what's possible Exploratory

“ What can I do with my data?”

You know AI belongs on the roadmap but haven't committed to specific use cases. We assess your data estate as it stands and work outward: which AI use cases it can support today, which come within reach after targeted changes, and how they rank by feasibility and value.

This is you if…

  • No confirmed AI use cases yet — you're exploring what's possible
  • Leadership wants an AI strategy grounded in your actual data, not hype
  • You suspect gaps in your data layer but don't know where they are

You leave with

  • Ranked map of AI use cases your data supports today
  • Use cases within reach after targeted remediation
  • 100 Point Check score and prioritized roadmap
Start with Exploratory
Validate your plan Confirmation

“ Can my data support the use cases we want?”

You already know the first-mover AI use cases you want. We start from those and work inward: whether your data, architecture, and governance can support them now, exactly what has to change if not, and a go, fix, or wait call for each one.

This is you if…

  • Specific use cases already identified and prioritized
  • Budget earmarked — you need evidence before committing it
  • A board or exec sponsor is asking "are we actually ready?"

You leave with

  • Per-use-case readiness verdict: go, fix, or wait
  • Gap analysis mapped to your target use cases
  • 100 Point Check score and prioritized roadmap
Start with Confirmation

Both engagement types are from $25K, run 2 weeks, and include the full Assessment deliverables. Not sure which fits? The discovery call sorts it in 30 minutes. Schedule a Discovery Call →

Our Approach

Three Tiers, One Outcome: Certainty

Start with a fast diligence read, prove it with a prototype, or scope a multi-agent build. Every tier is fixed-fee.

Tier 1: Assessment

A fast, fixed-fee diligence read. The 100 Point Check plus a vendor-neutral architecture blueprint and a go, fix, or wait recommendation. Offered in two engagement types — Exploratory or Confirmation — depending on your need and AI maturity. The lowest-risk way to know where you stand.

  • 100 Point Check readiness scorecard
  • Vendor-neutral architecture blueprint
  • Prioritized remediation roadmap
  • Evidence-based go, fix, or wait recommendation

Tier 2: Prototype (Most Popular)

Everything in the Assessment, plus a working prototype built on your real data. Readiness proven, not assumed, with a functioning proof of concept your team can evaluate.

  • Full Assessment deliverables
  • Working prototype on your real data
  • Technical validation of the target use case
  • Build recommendations and next-phase plan

Tier 3: Custom

A scoped engagement for multi-agent systems and production-grade builds, tailored to complex environments and larger AI programs.

  • Custom scope for multi-agent or production builds
  • Full architecture and data-layer design
  • Production-oriented prototype or pilot
  • Delivery roadmap and governance plan

Ready to Get Started?

Schedule a free 30-minute consultation — we'll confirm your data is a fit.

Schedule Free Consultation

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Engagement Details

Engagement Details

From $25,000

Investment

Fixed-fee, no hidden costs

2 to 12 weeks by tier

Timeline

From kickoff to delivery

Three tiers. Each ships something real.

Start where your question is sharpest. Each tier stands on its own.

Tier 1 · Diligence

Assessment

From $25K · 2 weeks

Architectural diligence of your data readiness. Maps the data landscape, identifies governance constraints, prioritizes feasible AI use cases, and delivers a vendor-neutral, build-ready blueprint. Available in two engagement types — Exploratory or Confirmation — depending on your need and AI maturity.

Most popular
Tier 2 · Headline

Prototype

$55K to $70K · 4 weeks

The headline engagement. A four-week architectural sprint that ships a production AI agent on your data, MCP-native and governance-first, in production by week 4. Not a strategy deck. A working agent.

Tier 3 · Multi-agent

Custom Scope

From $120K · 6 to 12 weeks

For companies deploying SparteraConnect at scale with integration into ERP, CRM, or warehouse systems. Multi-agent governance, custom validated query patterns, multi-team rollout, and SLA-backed handoff.

Optional Add-ons

The Spartera 100 Point Check as a standalone diagnostic
Additional prototype iterations
Data-layer remediation delivery
Progression into a Data Foundation or full build engagement
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What to Expect

What to Expect

Based on engagements with companies at similar stages. Individual results vary with data quality, use-case complexity, and internal readiness.

1

A clear go, fix, or wait decision

Most teams come in unsure whether their AI initiative is viable. They leave with a defensible readiness score and a specific recommendation, so budget goes to what's ready and not to what isn't.

2

A working prototype, not a slide deck

At the Prototype tier and above, you see a functioning proof of concept on your own data before committing to a full build, dramatically lowering the risk of the investment.

3

A prioritized remediation roadmap

Where gaps exist, you get a ranked plan to close them, so the path from where you are to production-ready is concrete rather than aspirational.

Ready to see what's possible for your data?

📅 Schedule Free Consultation
FAQs

Common Questions

How is this different from a generic AI consulting assessment?

Most assessments hand you a slide deck of opinions. We give you a weighted, defensible readiness score from the 100 Point Check, a vendor-neutral architecture blueprint, and, at the Prototype tier and above, a working prototype on your real data. You leave with proof and a decision, not a set of recommendations you still have to validate.

Which tier should we start with?

If you need to know whether an initiative is viable before committing budget, start with the Assessment. If you already believe in the use case and want to prove it on your data, go straight to the Prototype. The Custom tier is for multi-agent systems and production-grade builds. The discovery call confirms the fit.

What's the difference between the Exploratory and Confirmation assessment?

Scope, not price or duration. Exploratory starts from your data and works outward: we identify which AI use cases your estate can support and rank them by feasibility and value — right for teams that haven't committed to specific use cases yet. Confirmation starts from your use cases and works inward: you bring the first-mover use cases you want, and we assess readiness against exactly those, with a go, fix, or wait call for each. Both run two weeks, both include the 100 Point Check, the vendor-neutral blueprint, and the remediation roadmap, and both are the same fixed fee. The discovery call confirms which fits.

Do you need access to our raw data?

No. We work from your schema, architecture, and a defined use case. For the prototype, we use read-only access in your environment. Raw data does not need to leave your control, consistent with Spartera's zero-data-movement approach.

What is the Spartera 100 Point Check?

It's our weighted readiness diagnostic. It scores five dimensions, data, use case, security, management, and team, to produce a single, defensible readiness number and pinpoint exactly where the gaps are. It's the backbone of the Assessment and every higher tier.

What happens after the engagement?

You have a clear go, fix, or wait decision. If you're ready to build, we can progress into a Data Foundation or full build engagement. If gaps exist, you have a prioritized roadmap to close them. Either way, the next step is concrete.

Still have questions?

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Ready to Find Out If You're AI-Ready?

A 30-minute discovery call confirms the right tier and engagement type. From there, your readiness score and first blueprint can be in hand in as little as two weeks.

1

Discovery call

30 minutes to confirm your use case, engagement type, and the right tier

2

100 Point Check

We run the weighted readiness diagnostic and architecture review

3

Blueprint and prototype

Vendor-neutral blueprint, plus a working prototype where you're ready

4

Executive readout

Your score, roadmap, and a clear go, fix, or wait recommendation

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30-minute discovery call
Custom solution proposal