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.
of Fortune 500 CCOs are already using AI for comms. Less than a third have a strategy for it.
C-suite content generates 4x more engagement than content from any other role on LinkedIn.
No communications team can sustain a coordinated suite of outputs across six or more platforms without losing consistency or speed.
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.
First year social media became the primary news source for consumers. Trust in traditional media sits at a 30-year low.
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.
of what LLMs cite comes from corporate-owned 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.
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.
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.
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.
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.
Upland AI runs the approved narrative through every channel simultaneously.
When algorithms shift and GEO standards evolve, Upland AI updates.
Getting it out is only half the problem. Every channel has an algorithm, and every algorithm has preferences. LinkedIn rewards different structures than it did two years ago. Reddit surfaces credibility differently than a press release does.
AI search, now the first place many stakeholders encounter an executive's position, pulls primarily from corporate-owned content. If that content isn't there, the model infers it from whatever's in the public record.
Channel Format
Structured for each platform's native conventions and length expectations.
Algorithm Fit
Updated as platform ranking signals change, not locked at build time.
GEO Optimization
Built to current generative search standards so leaders control how they appear in AI results.
Audience Register
Tone and detail level calibrated per stakeholder, not reformatted by hand.
Upland AI stays current so the comms team 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
Nationally recognized leader & entrepreneur in media and communications. Executive responsibilities in corporate communications across politics, technology, finance, media and sports
Jessica Gang
Corporate communications advisor with experience working with technology companies at Brunswick Group and 3 years at Upland Workshop
Tanya Oskanian
COO, Upland Workshop since 2020
Previously Disney Pixar
Macrina Wang
Communications lead at an AI startup, previously a reporter at The Toledo Blade
Alex Barinka
C-Suite marketing and communications leader for multiple consumer technology companies and senior Bloomberg reporter covering deals and social media
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
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.