Enterprise AI Done Right

Artificial Intelligence Consulting

Vendor-neutral, operator-led AI implementation for private equity firms and middle-market companies. We help teams identify where AI can create real operating value, then move the best opportunities into governed, measurable execution.

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Moving AI From Pilot Programs to Scalable Business Impact

AI value comes from the workflow, not the model alone. The hard part is moving from isolated pilots to production use cases with clean data, clear owners, adoption plans, governance, and measurable operating KPIs.

TriVista helps teams identify where AI can change the way work gets done, then ranks use cases that have a real path to EBITDA impact, risk reduction, or faster decisions.

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Six Engagements
Built for PE and Operators

We help management teams, investors, and boards turn AI ambition into a focused operating plan with owners, governance, value tracking, and practical adoption steps.

01.

AI Value Creation Diligence
Assess AI opportunities, risks, data readiness, and implementation requirements before or during a transaction. Outputs include a quantified value thesis, risk register, and 100-day AI roadmap.
02.

AI Readiness & Risk Assessment
Evaluate whether the organization has the systems, data, workflows, governance, and talent to deploy AI safely. Outputs include readiness scoring, workflow maturity, and prioritized gaps.
03.

Vendor-Neutral Solution Selection
Compare model providers, copilots, enterprise platforms, vertical SaaS, automation tools, and open-source options without vendor incentive. Outputs include shortlist, TCO, security, and implementation comparison.
04.

90-Day AI Value Sprint
Implement one or two high-value use cases in a controlled environment with clear KPIs, operating owners, change management, and benefit tracking.
05.

AI Governance & Compliance
Establish practical AI policies, human-in-the-loop controls, vendor-risk processes, audit trails, data protections, and board-ready reporting.
06.

Portfolio AI Factory
Scale AI across multiple portfolio companies using repeatable use-case playbooks, governance templates, value dashboards, and sponsor-level reporting cadence.

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What Gets Built

Each engagement produces practical artifacts that help AI move from idea to operating model.

Core implementation outputs, including peer benchmarking:

AI Opportunity Backlog

A ranked list of use cases with estimated EBITDA impact, time to value, complexity, named owners, and the first move needed to validate each opportunity.

Workflow & Data Map

A practical view of where work happens today, what systems and data sources are touched, and which gaps need to be fixed before implementation.

Governance & Value Dashboard

A lightweight operating cadence for controls, adoption, KPI movement, benefit ownership, and board-level reporting after launch.

Peer Benchmark Matrix

A readiness view that benchmarks the business against industry peers across AI spend / revenue, named AI ownership, time-to-first-value, top use cases, and likely first engagement. The output helps leaders see whether they are aspirant, emerging, or ready to scale.

Industry Readiness Stat Strip

A concise benchmark of peer signals by industry, including AI spend / revenue, named AI leadership, time-to-first-value, and the top production use case where similar companies tend to start.

Readiness Positioning View

A visual map that compares readiness and ambition against peer bands, showing whether the business is an aspirant, observer, optimizer, or leader and where the biggest gap sits.

Recommended Engagement Path

A practical next-step recommendation tied to the benchmark result, from readiness assessment to value sprint to portfolio AI factory, with leader plays that show what strong peers are already doing.