Services

Three steps. The first one is free.

Most Soligence engagements follow the same pattern: a free intro call to see whether AI is the right lever, a two-to-four-week paid discovery that maps the work and prices the plan (credited in full toward project work), and then project work structured the way you and we agree is best.

Book an intro call See the three steps
How we work

Intro call, then discovery, then project work.

88% of organizations use AI. Single digits have it running in production.1 Each step below exists to close that gap: from a first conversation to a system your team runs.

Step 1: Intro call

Free · 30 to 45 minutes

A working conversation with a senior advisor, not a pitch. For CEOs, COOs, CFOs, operating partners, and business-unit leaders.

  • You describe the bottleneck and what you have tried
  • We tell you honestly whether AI is the right lever right now
  • Where it fits: what discovery would cover, what it would cost, and what it leads to
  • Open Q&A on Soligence, prior work, and how we build
Best for: deciding whether we are the right partner before anyone spends money

Step 2: Discovery

Paid · 2 to 4 weeks · starts at $5K

Structured interviews with your team, a review of the workflows, data, and controls involved, and a baseline of the value at stake. You leave with a plan you can fund or take elsewhere.

  • Recommendation memo and a readout or workshop with your leadership
  • Opportunity map: the two or three use cases most likely to produce measurable value
  • Value baseline and measurement plan for each
  • Roadmap, readiness scorecard, and a scoped proposal with timeline, deliverables, and pricing
  • Credited in full toward project work that begins within 60 days
Best for: knowing exactly what to build, what it is worth, and what it will cost before you commit

Step 3: Project work

Structured with you

Usually one of two things, often both: implementing Argus360 for the core customer and deal intelligence, and custom builds by our AI Factory, the senior engineering team and agent workflows that build what a module does not cover. The structure comes out of discovery; the four models below are the shapes it usually takes.

  • Senior engineers lead the work. No off-shore handoff, no junior bench
  • Acceptance gates tied to operating metrics, not demos
  • Documentation, training, and governance so your team runs it after launch
  • Outcome-aligned fees available when the outcome can be verified
Best for: a working system in production, run by your team or licensed from ours
Step 3, four ways

How project work gets structured.

Whether the work is an Argus360 implementation, an AI Factory custom build, or both, discovery tells us which of these commercial shapes fits. Where a pattern exists, we use Catalyst playbooks to accelerate scope, delivery, acceptance gates, and handoff.

6-Week Sprint

Fixed price, fixed scope

One production-ready AI workflow, delivered in six weeks at an intense pace.

  • Collaborative scope definition up front
  • Integration, documentation, handoff, and success metrics included
  • Outcome-aligned fee structures available when value can be verified
Best for: a focused, high-impact initiative with urgency

Custom Build

Defined scope, fixed price, agreed timeline

For multi-phase initiatives that do not fit the sprint model: a new system, a platform replacement, a modernization program.

  • Scope and deliverables defined in writing
  • Milestone-based timeline
  • Optional base fee plus capped success fee for measurable savings
Best for: multi-phase or atypical engagements

AI Operations Partnership

Fixed monthly price, flexible scope

We help operate, tune, and expand AI workflows as priorities evolve, join your operating cadence, and transfer the playbook to your team.

  • Ongoing optimization across AI initiatives
  • Dashboard review of adoption, cost, quality, and throughput
  • Terms from 3 months to 12+ months
Best for: sustaining value after launch

Fractional CAIO

Part-time Chief AI Officer

A named senior leader embedded in your C-suite for AI strategy and deployment. Joins leadership meetings, keeps the roadmap moving, and turns decisions into shipped systems.

  • AI strategy, roadmap ownership, and governance
  • Use-case evaluation, vendor guidance, board prep
  • Commercial model guidance for build-vs-buy and outcome-based contracts
Best for: strategic AI leadership at advisory pricing
What lands at the end

How this differs from a strategy-only AI engagement.

Not every consultancy works the way the left column describes, but enough do that it is worth asking these questions before you sign with anyone, including us.

Often, with a strategy-only consultancy Soligence
What you get at the end A roadmap and a deck; the build is someone else's job A working system in production, plus the roadmap
Who does the building Frequently a separate implementation vendor or offshore team The senior engineers who scoped it
Time to a working system Discovery can run for months before anything is built Discovery in 2 to 4 weeks, then a first workflow in production about 6 weeks after it starts
Who owns it afterward Varies by vendor and platform; worth asking Custom builds are handed to your team with documentation and training; Argus360 is licensed and hosted by Soligence
After launch Often a new statement of work Your team runs it, or we stay on under an operations partnership
Pricing Often hourly, where scope can drift Fixed price per step; capped success fees where the outcome can be verified
Inside the steps

What discovery and project work can include.

Focused working sessions we run as part of discovery or project work, or on their own under a fixed-scope SOW when a team needs one answer before it commits.

AI risk readiness

The security, compliance, and approval questions leadership should settle before budget is committed, with regulatory context (HIPAA, GLBA, GDPR, SOC 2). A framing session, not an audit or attestation.

Adoption and operating model

How AI actually gets adopted inside the business: roles, handoffs, incentives, ownership, and the training and adoption barriers to surface early.

Use case ideation

A cross-functional workflow review that produces a prioritized opportunity map through an ROI, feasibility, and urgency lens.

Vendor and platform strategy

Build-versus-buy, vendor fit, pricing models, and lock-in tradeoffs before you commit to a stack. We are an OpenAI Select Partner, and our recommendations stay vendor-neutral.

Agent orchestration design

Agent inventory, tool access, routing, observability, human-in-the-loop gates, and escalation rules mapped before you build more than one workflow.

Reliability review and post-launch operations

An independent assessment of how an existing AI system performs under real conditions, and the monitoring, tuning, and governance cadence once it is live.

Hands-on training

AI Training for Leaders and Teams.

Hands-on training for the work your team actually does. Delivered through Soligence Elevate, with real workflows, practical playbooks, and follow-up support.

What you get

  • Hands-on training, no theory or AI 101 slides
  • Real workflows around your actual work
  • Personal AI playbook built in session
  • Follow-up support after the intensive

What you can book

  • Private team intensive (everyone aligned on how AI gets used)
  • Individual seats in upcoming public sessions
  • Custom enterprise track for larger orgs
  • Manager and leadership tracks
Visit Soligence Elevate
Common questions

Frequently asked questions

The intro call is free. Discovery is a fixed fee that starts at $5K and is credited in full toward project work that begins within 60 days. Project work is priced per engagement: a fixed-price 6-Week Sprint, a fixed-price Custom Build, a monthly AI Operations Partnership, or a Fractional CAIO retainer. When relevant, we model build-vs-buy tradeoffs against your current vendor spend so the investment case is clear.
Yes, when the outcome can be measured cleanly. We usually recommend a fixed base fee plus a capped success fee tied to agreed, verified business outcomes. Good candidates include cycle-time compression, throughput improvement, fewer operational misses, lower rework, software spend optimization, risk reduction, and customer-retention or expansion gains. We avoid vague ROI claims and top-line attribution unless the measurement model is clear before work begins.
Structured interviews with your team, a review of the workflows and data involved, and a written assessment. You receive a recommendation memo and a readout or workshop, an opportunity map, a value baseline and measurement plan, a roadmap, and a scoped proposal with timeline, deliverables, and pricing. The plan is yours whether or not you go on to project work with us.
It applies to custom builds: your team owns and runs the system when we leave. We document everything, train your people, and structure governance so you can operate and evolve the workflows without us. That ownership is 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. Argus360 is different and we say so up front: it is licensed and hosted by Soligence, so you get a maintained platform and a vendor relationship, the same as any licensed software, rather than a codebase to run yourself.
Discovery runs two to four weeks depending on scope. A 6-Week Sprint delivers a production-ready workflow in six weeks. Custom Builds and AI Operations Partnerships are scoped to your timeline, and Fractional CAIO engagements typically run several months or longer. We will help you select the right pace during the intro call.
Private equity firms and their portfolio companies, insurance carriers, and similar operationally intensive businesses: asset managers, investment banks, and professional services firms. Our clients share a profile: operationally intensive businesses with high data volume where manual effort is the bottleneck. See our Private Equity and Insurance pages, or the industries overview.
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

Book the intro call.

Tell us the bottleneck. We'll tell you whether AI is the right lever, and if it is, what discovery would cover.

Step 1 · Free

Intro call

30 to 45 minutes. You describe the bottleneck; we tell you honestly whether AI is the right lever and what discovery would cover. No deck, no pitch.

Step 2 · Paid, credited

Discovery

Two to four weeks. We map the workflows, data, and controls, baseline the value, and return a scoped plan with timeline and pricing. Starts at $5K, credited in full toward project work that begins within 60 days.

Step 3 · Shaped together

Project work

Argus360 for the core customer and deal intelligence, custom builds by our AI Factory for what a module does not cover. Structured the way you and we agree is best: a fixed-scope sprint, a multi-phase build, an ongoing operations partnership, or fractional AI leadership.

Most engagements follow this pattern. See how we work.

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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.