How do you handle governance and AI risk?

Security and governance are design requirements from day one, not features added later. Documented AI incidents rose roughly 55% year over year in 2025 (362 incidents, up from 233) and frontier-model responsible-AI reporting remains spotty (Stanford HAI, AI Index 2026). We design for your risk posture — not against a generic checklist.

Engagements

Choose the engagement that matches your urgency.

Our services are structured to move quickly without sacrificing rigor. Every engagement transfers real capability to your team.

View offerings See our workshops

How we work

Engagement options

88% of organizations use AI. Single digits have it running in production.¹ Every engagement below is designed to close that gap — ordered from lowest to highest commitment.

Free Intro Call

No commitment

30–60 minute call to understand your needs and explain how we work.

Honest read on whether AI fits your situation
Overview of Soligence and prior work
Open Q&A with a senior advisor

Best for: exploring whether we're the right partner

Paid Discovery

Low commitment

Structured assessment that answers your most important AI questions before you commit.

Focused — 1 week: single use case, recommendation memo, 60-min readout
Standard — 2 weeks: 2–3 use cases, opportunity map and memo, 90-min workshop
Deep — 4 weeks: portfolio review, roadmap, readiness scorecard, half-day workshop
100% of fee credited toward any engagement signed within 60 days

Best for: de-risking the decision to invest

6-Week Sprint

Medium commitment

Fixed price, fixed scope, intense pace. Scope is defined collaboratively, then locked into a fixed scope box.

Collaborative scope definition up front
Production-ready AI workflow delivered in 6 weeks
Integration, documentation, and handoff included

Best for: a focused, high-impact initiative with urgency

Traditional SOW

Medium Commitment

Defined scope, fixed price, agreed timeline. For initiatives that don't fit the sprint model.

Scope and deliverables defined in writing
Fixed price tied to agreed scope
Milestone-based timeline

Best for: multi-phase or atypical engagements

Retainer

Tactical · high commitment

Fixed monthly price, flexible scope. We work together to direct hours where they deliver the most value as priorities evolve.

Monthly retainer with flexible scope
Tactical execution support across AI initiatives
Terms from 3 months to 12+ months

Best for: ongoing hands-on AI delivery capacity

Fractional CAIO

Strategic · high commitment

Part-time Chief AI Officer — a named senior leader embedded in your C-suite for AI strategy and deployment.

AI strategy, roadmap ownership, and governance
Use-case evaluation, vendor guidance, competitive analysis
Staff education, board prep, leadership meeting participation

Best for: strategic AI leadership at advisory pricing

Fixed-Scope Workshops

High-value workshops we deliver

These workshops can stand alone under SOW or lead into a sprint, retainer, or fractional leadership engagement. Each one is designed to produce a concrete outcome: an aligned leadership view, a prioritized opportunity map, a vendor recommendation, or a clearer operating plan.

Executive Briefing

Phase 01 · Leadership alignment

A concise briefing for executives who need a clear view of where AI is creating value, where the risks sit, and what to do next.

Market context tailored to your business model
Board and leadership talking points
Recommended next moves and decision points

Best for: aligning the C-suite before budget or vendor decisions

Adoption and Operating Model Workshop

Phase 02 · Change readiness

A working session focused on how AI actually gets adopted inside the business, including roles, handoffs, incentives, and ownership.

Role and workflow changes mapped clearly
Training and adoption barriers surfaced early
Recommended operating model for rollout

Best for: teams that need more than training to make AI stick

Use Case Ideation

Phase 03 · Opportunity mapping

A working session to identify, prioritize, and scope the AI use cases most likely to produce measurable operational value.

Cross-functional workflow review
Prioritized opportunity map
ROI, feasibility, and urgency lens

Best for: choosing the right first and second bets

Vendor and Platform Strategy

Phase 04 · Platform decisions

A structured review of build-versus-buy choices, vendor fit, pricing models, and platform tradeoffs before you lock into a stack.

Vendor shortlist and evaluation criteria
Build-vs-buy and lock-in tradeoff analysis
Pricing and commercial model review

Best for: buyers who want an independent point of view before signing

AI Reliability Review

Phase 05 · Risk and validation

An independent assessment of how an existing AI system performs under real conditions, where it can fail, and what must change before scale.

Workflow, prompt, and model review
Failure mode and drift analysis
Remediation priorities with executive readout

Best for: teams that have shipped AI but need confidence in reliability

AI Operations and Optimization

Phase 06 · Post-launch performance

A post-launch workshop focused on how AI systems get monitored, tuned, governed, and improved once they are live in the business.

Monitoring, escalation, and review cadence
Prompt, model, and workflow optimization plan
Governance guardrails for ongoing operations

Best for: organizations that need an answer to what happens after go-live

Common questions

Frequently asked questions

We start with a free intro call, then typically a paid discovery to align on scope and confirm fit. Delivery usually happens through one of four models: a 6-Week Sprint, a Traditional SOW, a Retainer, or a Fractional CAIO engagement. When relevant, we also model build-vs-buy tradeoffs against your current vendor spend to ensure the investment case is clear.

We don't hand you a deck and walk away. We co-build alongside your team and transfer ownership of the system, the decision logic, and the roadmap. Our own business runs on the same AI-native architecture we deploy for clients.

It means your team owns the system when we leave. We document everything, train your people, and structure governance so you can operate and evolve the AI workflows independently. You keep the capability, not the dependency. It's also a labor-market hedge — inbound migration of AI researchers and developers to the U.S. is down 89% since 2017, and U.S. developers ages 22–25 saw employment fall nearly 20% from 2024.² Renting capability gets more expensive every quarter. Owning it compounds.

Paid Discovery runs 1–4 weeks depending on depth. A 6-Week Sprint delivers a production-ready workflow in six weeks. Traditional SOWs and Retainers are scoped to your timeline, and Fractional CAIO engagements typically run several months or longer. We'll help you select the right pace during the intro call.

Discovery combines structured interviews with your team and a written assessment. You receive a recommendation memo and a readout or workshop — and for Standard and Deep tiers, an opportunity map or roadmap you can share with stakeholders. 100% of the discovery fee is credited toward any engagement signed within 60 days, so it de-risks the decision without adding cost.

PE portfolio companies, investment banks, insurance carriers, and professional services firms. Our clients share a profile: operationally intensive businesses with high data volume where manual effort is the bottleneck. See our industries page for details.

That's common. Most AI pilots fail because they skip governance, adoption design, and team enablement. We address all three from day one so the system actually gets used and delivers sustained value.

Security and governance are design requirements from day one, not features added later. Documented AI incidents rose roughly 55% year over year in 2025 (362 incidents, up from 233),³ and frontier-model responsible-AI reporting remains spotty. We design for your risk posture — not against a generic checklist.

Yes. We design solutions around your constraints and data, not around a specific vendor or platform. We're tool-agnostic and integrate with what you already have.

The enterprise software landscape is shifting from seat-based to usage and outcome-based pricing. This creates both savings opportunities and new complexity. As part of our solution design process, we model total cost of ownership across build-vs-buy decisions, evaluate vendor lock-in risk, and help you negotiate contracts aligned with actual value delivered.

Next step

Let us scope the right engagement.

We'll propose a path that matches your urgency, risk tolerance, and internal capacity.

How it works: 30-minute discovery call (no pitch deck) → we tell you honestly if AI fits your situation → if it does, you get a scoped proposal with timeline, deliverables, and pricing within one week.

Sources
1. Stanford Institute for Human-Centered AI, Artificial Intelligence Index Report 2026, April 2026 — organizational AI adoption (88% in 2025, up from 78% in 2024) and AI agent deployment rates by business function.
2. Stanford Institute for Human-Centered AI, Artificial Intelligence Index Report 2026, April 2026 — inbound migration of AI researchers and developers to the U.S. (89% decline since 2017; 80% decline in the last year alone) and U.S. software developer employment ages 22–25 (nearly 20% decline from 2024).
3. Stanford Institute for Human-Centered AI, Artificial Intelligence Index Report 2026, April 2026 — AI Incident Database: 362 documented incidents in 2025, up from 233 in 2024.