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For founders and CEOs

AI Consulting for Founders and CEOs

AIDOLS helps founders and CEOs ship the AI roadmap the board asked for in 90 days — without committing to a $500K AI hire before validation. Each engagement is scoped against a specific competitive thesis, ships a production system inside one quarter, and produces the artifact set the next board meeting needs: a working product, a defensible architecture, and a written ROI verification.

90
Days to Production
100%
ROI Guarantee
$15K
Sprint starting fee

What founders and CEOs get from AIDOLS

Specific outcomes scoped against the metrics the founder office already tracks — not generic value props.

Outcome 1

A board-ready AI thesis without committing to a permanent hire

AIDOLS Sprint engagements ($15K-$25K) produce the prioritized roadmap, the target architecture, and the build sequence the board needs to greenlight the AI thesis — without committing to a $250K-$500K Head of AI hire before the thesis is validated. Founders get a defensible artifact for the next board meeting in 2-3 weeks.

Outcome 2

Production AI shipped inside one quarter

AIDOLS Build engagements ship the first production AI system in 90 days against a written KPI. Founders move from board pitch to deployed feature inside one fiscal quarter, with the engineering team free to focus on the core product roadmap rather than an AI infrastructure detour.

Outcome 3

No proprietary lock-in. The IP stays with you.

AIDOLS hands over source code, model weights, evaluation datasets, and infrastructure-as-code at the close of every Build. Founders own the IP, can fundraise on the technology without disclosing a vendor dependency, and can take the system entirely in-house once the team is hired.

Outcome 4

A capability bridge while you hire

A senior AI hire takes 4-9 months and $250K-$500K fully loaded. AIDOLS' Scale tier ($25K/month) bridges the gap: production AI capability immediately, transition to the in-house team once they're hired and trained. Founders avoid the chicken-and-egg problem where AI hiring waits on AI capability and AI capability waits on AI hiring.

The 4 problems we solve for founders and CEOs

Your board asked for an AI roadmap. You do not have a Head of AI to write one.

Most growth-stage founders face the same dynamic post-Series B or post-Series C: the board asks for an AI roadmap, the existing engineering leadership has no AI specialization, and the cost of a Head of AI hire ($250K-$500K fully loaded, 4-9 month time-to-fill) is hard to defend before the thesis is validated. The default outcome is a slide deck the founder writes themselves, which the board accepts but does not action.

AIDOLS Sprint engagements produce a defensible AI roadmap in 2-3 weeks: prioritized opportunity map, target architecture, build sequence, written ROI projection per use case, and a 90-day Build SOW for the highest-priority candidate. Founders walk into the next board meeting with a working artifact set, not a personal opinion.

Benchmark: 2-3 week roadmap delivery vs. 4-9 month Head of AI hiring cycle. $15K-$25K Sprint vs. $250K-$500K hire commitment.

Your competitors are shipping AI features. You cannot wait 12 months to respond.

In most growth-stage software and services markets, competitive AI feature releases compress the response window from 12 months to 90 days. Founders who try to respond by hiring an in-house AI team typically lose the window — the team takes 6 months to assemble and another 6 months to ship the first feature, by which time the competitor has shipped two more.

AIDOLS Build engagements ship a production AI feature inside 90 days against a written KPI. Founders defend or expand competitive position inside one quarter rather than ceding two release cycles to the competitor. The in-house team can be hired in parallel and inherit a working system instead of starting from scratch.

Benchmark: 90-day production cutover vs. 12-month industry median for first AI feature ship in a growth-stage company. AIDOLS frequently runs Builds in parallel with the in-house AI hiring process.

You cannot raise on AI capability you do not have. You cannot have it without spending.

In Series B and Series C fundraising cycles, AI capability is increasingly a fundability question. Founders need a defensible AI story for the deck and ideally a deployed feature investors can see. Building the capability ahead of the round requires committing capital that cannot be recovered if the round does not close; not building it risks the round entirely.

AIDOLS Build engagements ship a production AI feature in 90 days at $75K-$150K — comparable to one quarter of a senior engineer's loaded cost, recoverable inside the round if it closes, and defensible to investors as a capital-efficient capability buildout. Founders fundraise on a working product, not a slide deck.

Benchmark: $75K-$150K Build fee vs. $250K-$500K fully-loaded senior AI hire. 90-day production cutover positions the AI capability for the next fundraise.

You cannot defend AI spend if growth contracts mid-quarter.

In a slower growth or recessionary environment, multi-quarter consulting retainers and permanent AI hires are the first line items reviewed. Founders who have committed to either ahead of validation face the choice between cutting the program (writing off the spend) and continuing it (defending it on a quarter-by-quarter basis to the board).

AIDOLS structures engagements as discrete units. A Sprint clears or it does not. A Build ships or refunds. Scale renews monthly with 60-day cancellation notice. Founders can pause without writing off committed spend and without unwinding a permanent headcount commitment.

Benchmark: 60-day cancellation notice on Scale; no multi-quarter prepayment; full Build fee refund if the agreed KPI is not cleared inside 12 months of cutover.

Get your AI Readiness Score in 5 minutes

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How a founder engagement typically works

Four steps from kickoff to production cutover. Fixed fee at every step.

Step 1Week 1

Founder + leadership kickoff

Joint workshop with the founder/CEO and the operating leadership (CTO/COO/Head of Product as applicable). Agree the competitive thesis, the KPI tied to the 100% ROI guarantee, and lock the SOW.

Step 2Weeks 2-4

Architecture + product integration

AIDOLS engineers design the production architecture inside your existing stack and the integration into the core product surface. Architecture decision records produced for your engineering team to keep.

Step 3Weeks 5-8

Build + product surface

Model and product integration built in parallel. Weekly demo to the founder and the product team. PRs land in your repo. Working feature visible inside the product UI by Week 8 for internal testing.

Step 4Weeks 9-12

Production launch + KPI verification

Feature launch to production users (canary then full rollout). KPI verified against baseline for 30 days post-launch. Optional Scale retainer or transition to the in-house team. Source, weights, IaC handed over.

Pricing model that fits a founder's budget cycle

Three transparent fixed-fee tiers — no time-and-materials drift, no partner-leverage uplift, no surprise change orders.

Sprint
$15K-$25K USD
2-3 weeks

Best for: Founders scoping the AI roadmap the board asked for. Produces an artifact set that supports the next board meeting and a Build SOW for the priority use case.

  • Data + infrastructure audit
  • Prioritized opportunity map with ROI estimates per use case
  • Target-state reference architecture
  • 90-day implementation roadmap with named owners
  • Executive readout deck
Build
$75K-$150K USD
90 days

Best for: Founders ready to ship one production AI feature in 90 days against a competitive thesis. Carries the 100% ROI guarantee and full IP handover.

  • Production AI system shipped end-to-end
  • Data engineering, model development, MLOps deployment
  • Integration into existing systems
  • Post-launch evaluation harness + monitoring
  • 100% ROI guarantee against a written KPI
Scale
$25K/month USD
12-month minimum

Best for: Founders running production AI who want a fixed monthly capability line item while the in-house team is hired or while the company stays capital-efficient.

  • Ongoing engineering retainer post-deployment
  • Model retraining, monitoring, drift detection
  • Incident response + evaluation harness updates
  • One new feature release per month
  • Replaces a $250K-$350K fully-loaded MLOps hire

AIDOLS vs Big Four for a founder

DimensionAIDOLSBig Four
Pricing modelFixed fee per tier; written, no T&M driftTime-and-materials retainer; partner-leverage uplift
Engagement size$15K-$150K per engagement; recoverable inside next fundraise$500K-$2M+ retainers; not defensible to growth-stage board
DeliverableProduction AI feature visible in product UIStrategy deck + roadmap; implementation handed off separately
Time to production90 days end-to-end6-18 months across phased SOWs
IP ownershipSource + weights + IaC transfer at SOW closeOften proprietary platform; lock-in disclosed at fundraise
Board defensibility100% ROI guarantee against written KPI; verifiable at board meetingHours billed; outcomes disclaimed; difficult to defend at QBR
Hiring postureBridges to in-house team without permanent commitment day oneOften recommends $500K-$2M permanent capability buildout
Exit clarity60-day cancellation on Scale; clean handoverAnnual prepayment + termination fees

What a founder should ask before hiring an AI consulting firm

Seven questions to put on every shortlist call. Firms that cannot answer crisply on all seven are not engineering-first.

  1. What is the fixed fee, the timeline, and the written KPI tied to the 100% ROI guarantee?
  2. Do we own the source code, model weights, and infrastructure-as-code at SOW close?
  3. Who personally is on the engagement, and do they stay on after the SOW is signed?
  4. How does the firm handle the transition to an in-house team once we hire?
  5. How many production AI systems has the firm shipped at growth-stage companies in the last 12 months?
  6. Can I see a working production deployment from a comparable Series B/C client (under NDA)?
  7. What is the cancellation clause if our growth contracts mid-engagement or if a fundraise slips?

Calculate your AI ROI before you sign anything

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Common objections from founders and CEOs — and our honest answers

Objection 1

"We should just hire a Head of AI."

You probably should — eventually. The hire takes 4-9 months at $250K-$500K loaded and is hard to defend before the AI thesis is validated. AIDOLS Sprint + Build sequence validates the thesis and ships the first system inside one quarter at $90K-$175K total, and bridges the capability gap with a Scale retainer until the in-house team is up. Most founders run AIDOLS in parallel with the hiring process, not instead of it.

Objection 2

"Our investors will see this as outsourcing core capability."

Investors mostly want to see a working product and a defensible thesis. AIDOLS engagements ship the working product and hand over the IP — source, weights, IaC. Most growth-stage investors view the pattern (90-day Build + bridge to in-house team) as capital-efficient capability buildout, not outsourcing.

Objection 3

"We tried a freelance AI consultant. The notebook never made it to production."

Freelancers solve a model-development problem; production deployment requires data engineering, MLOps, integration, and evaluation in parallel. A typical 90-day production deployment runs 600-900 engineering hours, which at freelance rates totals $90K-$360K — comparable to or higher than the AIDOLS Build tier — without the team coverage.

Objection 4

"$75K-$150K is more than I want to commit before validation."

Start with a Sprint at $15K-$25K. The output is the artifact set the next board meeting needs and a fixed-fee Build SOW for the priority use case. If the Sprint kills the thesis, you spent 2-3 weeks of executive attention and saved a quarter of capex.

Objection 5

"Our engineering team will not accept an outside firm in the codebase."

AIDOLS works alongside your engineering team rather than around them. PRs land in your repo, architecture reviews include your CTO and principal engineer, and the on-call runbook is written for your team to operate. Most engagements are co-sponsored by the CTO precisely because the fixed-fee model removes the budget risk that usually creates internal friction.

Three anonymized founder engagement patterns

Generic descriptors used to protect client confidentiality. Detailed reference architectures and named references available under NDA.

Pattern 1

Series B SaaS founder

Series B SaaS founder engaged AIDOLS to ship an in-product AI copilot ahead of a Series C raise. KPI: copilot adoption among paid users + per-session inference cost ceiling.

Result: Production launch in 78 days; copilot adoption hit 41% among paid users by day 120, NPS rose 11 points, and the feature directly attributed roughly $2.1M ARR in expansion + reduced churn. Founder closed Series C 5 months later with the copilot featured prominently in the deck.
Pattern 2

Series C marketplace founder

Founder of a Series C two-sided marketplace engaged AIDOLS for a Sprint-scope AI roadmap ahead of a board meeting where the AI thesis was the headline question. Scope: prioritized opportunity map, target architecture, build sequence.

Result: Sprint output identified two highest-priority Build candidates with payback projections, killed three other use cases on data-quality or competitive grounds, and produced a 12-month sequenced roadmap. Board approved the first Build at the same meeting; production cutover 90 days later.
Pattern 3

Series A B2B founder

Series A B2B founder engaged AIDOLS to bridge AI capability while hiring a Head of AI. Scope: 90-day Build of an AI-driven onboarding flow, then Scale retainer until the Head of AI was hired and the team was in place.

Result: Build shipped in 90 days; onboarding completion rate rose 34%, time-to-first-value dropped 62%. Scale retainer ran 7 months while Head of AI was hired and a 4-person team assembled; transition to in-house team complete 10 months from initial engagement, with no proprietary platform to migrate off.

FAQs from founders and CEOs

Should I hire AIDOLS or hire a Head of AI?

Most growth-stage founders should do both — sequenced. Use AIDOLS to validate the AI thesis with a Sprint ($15K-$25K, 2-3 weeks) and ship the first production system with a Build ($75K-$150K, 90 days) while the in-house Head of AI hire runs in parallel (4-9 months, $250K-$500K loaded). Once the in-house team is up, transition operations under a Scale retainer wind-down.

How does AIDOLS handle IP ownership?

AIDOLS hands over source code, model weights, evaluation datasets, and infrastructure-as-code at the close of every Build. Founders own the IP, can fundraise on the technology without disclosing a vendor dependency, and can take the system entirely in-house once the team is hired. There is no proprietary AIDOLS platform to migrate off.

How does AIDOLS pricing fit a growth-stage budget?

Sprint engagements at $15K-$25K typically clear single-signature founder authority. Build engagements at $75K-$150K are comparable to one quarter of a senior engineer's loaded cost and recoverable inside the next fundraise if it closes. Scale retainers at $25K/month with 60-day cancellation are easy to pause if growth contracts mid-quarter.

Can AIDOLS ship a feature in time for our next board meeting?

A Sprint ships in 2-3 weeks and produces a board-ready artifact set: prioritized opportunity map, target architecture, written ROI projection per use case, and a Build SOW for the priority candidate. A Build ships a production feature in 90 days. Most founders use the Sprint to greenlight the Build at the next quarterly board meeting and present the working feature at the meeting after.

What does the typical AIDOLS engagement look like for a Series B SaaS founder?

The modal Series B engagement is a Sprint to scope the AI roadmap ahead of the next board meeting, a Build to ship one production AI feature in 90 days against a written KPI, and a 6-12 month Scale retainer to bridge ongoing MLOps capacity while the Head of AI is hired and the in-house team is assembled. Total committed spend over 12 months: typically $200K-$400K vs. $400K-$800K for a fully-loaded in-house AI team in year one.

How does AIDOLS work alongside our existing engineering team?

AIDOLS works inside your engineering team's reference architecture, not around it. PRs land in your repo, architecture reviews include your CTO and principal engineer, and the on-call runbook is written for your team to operate. Most engagements are co-sponsored by the CTO precisely because the fixed-fee + ROI guarantee removes the budget risk that usually creates internal friction.

What happens if our fundraise slips or growth contracts mid-engagement?

Sprint engagements are 100% billed at kickoff and complete in 2-3 weeks. Build engagements bill 50% at kickoff and 50% at production deployment, with the second tranche subject to the ROI guarantee. Scale retainers bill monthly with 60-day cancellation notice. Founders can pause without writing off committed spend and without unwinding a permanent headcount commitment.

Can I show an AIDOLS-built feature to investors as our own technology?

Yes. AIDOLS hands over source code, model weights, evaluation datasets, and infrastructure-as-code at SOW close, and the engagement is structured as a work-for-hire with full IP transfer. Most growth-stage investors view the pattern as capital-efficient capability buildout. Reference founders can speak to the investor experience under NDA.