Upland AI

The executive voice infrastructure for enterprise leadership teams.

Executive voice is the highest-performing content in the enterprise. No one has figured out how to scale it.

96%

of Fortune 500 CCOs are already using AI for comms. Less than a third have a strategy for it.

4x

C-suite content generates 4x more engagement than content from any other role on LinkedIn.

6+

No communications team can sustain a coordinated suite of outputs across six or more platforms without losing consistency or speed.

Left behind.

Organizations that don't fill this gap will find it filled for them. AI infers positions no one authorized. Competitors publish more, the narrative moves without them.

The production infrastructure to meet demand doesn't exist yet.

The window for owning this category is open.
The conditions creating it won't reset.

2025

First year social media became the primary news source for consumers. Trust in traditional media sits at a 30-year low.

81%

of comms leaders report greater pressure to do more with fewer resources. Legal, security, and IP risk are the primary barriers to AI adoption, not appetite for the technology.

60%

of what LLMs cite comes from comms-managed content. Every week a leadership voice goes unheard, the narrative gap gets filled by AI inference, not by the executive.

The bottleneck isn't demand. It's infrastructure.

A purpose-built application layer with three capabilities generic LLM deployments can't replicate.

Voice icon

Executive Voice
Profiles

Learns from each leader's existing body of work and builds a dedicated voice model per executive, trained on their existing body of work.

Every approved edit sharpens voices across the enterprise. In time, no competitor can replicate it from scratch.

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Security icon

Enterprise Security
Architecture

Fully closed environment: SOC 2 compliant, client data never used to train public models, nothing accessible outside the client's team.

Built for materials that cannot touch a general-purpose tool: earnings drafts, M&A communications, board memos.

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Deployment icon

Multi-Platform
Deployment

One approved narrative deploys across every channel simultaneously, formatted for each platform and audience.

Built to current GEO (generative engine optimization) standards, so leadership controls how they appear in AI search results, not just human ones.

The longer an enterprise uses Upland AI, the harder it is to replace.

Proprietary Voice Model

Owned by your organization. Trained only on you.

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Source materials ingested

Past speeches, earnings calls, articles, op-eds, memos.

Voice profile built

Tone, cadence, audience calibration per executive.

Content produced

Any format, any channel, any audience.

Review & Approval

Corrections and edits absorbed back into the profile.

Profile sharpens

Approved narratives get more precise with every cycle.

Each pass tightens the loop. At twelve months, the profiles are proprietary. At eighteen it's enterprise infrastructure.

The right message for every audience, on every channel.

When a CEO makes an announcement, it doesn't go to "the market." It goes to investors, employees, press, board, and customers, each expecting a different frame, a different level of detail, and a different read on what it means for them.

It needs to show up across every channel, formatted for each platform's conventions. Comms teams will typically manage this with a manual reformatting process.

Audience
Investors
Employees
Press
Board
Customers
Regulators
Approved Narrative
Channel
LinkedIn
Reddit
Press release
All-hands
Board memo
Earnings

Upland AI runs the approved narrative through every channel simultaneously.

Comms teams can produce AI sources. Upland AI optimizes for GEO.

Every channel has an algorithm, and every algorithm has its own ranking signals. LinkedIn rewards different structures than it did two years ago. Reddit surfaces credibility differently than a press release.

AI search is increasingly the first place stakeholders encounter an executive's position, and it pulls primarily from comms-managed content. When that content isn't there, the model infers from whatever's in the public record.

Categories AI cites in generative search results:

  • Journalistic: News sites and other journalistic coverage
  • Third Party Corporate/Blog (Earned)*: Third-party corporate blogs and content not owned by the company in the query
  • First Party Corporate/Blog (Owned)*: Corporate content created by the company in the query
  • Press Release*: Press releases published on any site
  • Academic/Research: Scientific journals, arXiv, patents, research papers
  • Government/NGO: .gov sites, public agencies, non-profit organizations
  • Social/UGC*: Social platforms (LinkedIn, Reddit) and other user-generated content
  • Aggregators/Encyclopedic: Wikipedia, Visual Capitalist, Britannica
  • Tech Platforms: App stores

*Upland AI optimizes

Upland AI keeps GEO current so comms doesn't have to.

Upland AI was built by a team of professionals with decades of experience in communications, journalism, and media across politics, finance, entertainment, technology and sports.

Adam Mendelsohn

Adam Mendelsohn

Nationally recognized leader & entrepreneur in media and communications. Executive responsibilities in corporate communications across politics, technology, finance, media and sports

Jessica Gang

Jessica Gang

Corporate communications advisor with experience working with technology companies at Brunswick Group and 3 years at Upland Workshop

Tanya Oskanian

Tanya Oskanian

COO, Upland Workshop since 2020
Previously Disney Pixar

Macrina Wang

Macrina Wang

Communications lead at an AI startup, previously a reporter at The Toledo Blade

Alex Barinka

Alex Barinka

C-Suite marketing and communications leader for multiple consumer technology companies and senior Bloomberg reporter covering deals and social media

Lola Kolade

Lola Kolade

Strategic communications and public affairs lead in financial services and government. Previously a screenwriter with experience in scripted development at NBCUniversal International Studios.

Tahir Nawaz

Tahir Nawaz

Senior AI Engineer specializing in LLM/RAG systems, full-stack development, and ML pipelines, with research interests in document intelligence, computer vision, and applied deep learning.

“Upland AI has allowed me to expand the range of executives I support, while sharing content ideas and copy more quickly and efficiently. It has saved our team a significant amount of time and will continue to make our process smoother, helping us consistently hit the right tone of voice for each executive.”

Vanessa Azzi, Social Growth and Community Strategist I, United Wholesale MortgageUpland AI Client #1

Own the narrative.

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