Project Cobalt
A product management consultancy available for acquisition
Profitable and founder-led, it runs product management for Fortune 100 software programs and has built its own AI software.
Fortune 100 clients and its own AI software
Fortune 100 product organizations hire the Company to work out exactly what a new or rebuilt system must do: the business processes, data and rules behind it. Its teams turn that into the plans engineers build from, then build and integrate the systems, under multi-year agreements. Programs are large and long-running, and its own AI software speeds up the documentation behind them.
The Company’s teams sit inside each client’s product organization and run its internal systems day to day.
Its senior team has led this work on large enterprise programs for many years. Delivery and the AI software share one documented way of working.
What the Company does
Product Management
Senior product managers and analysts work inside client product teams and define what large programs must deliver. Clients adopt the Company’s practices into how their own teams work. About 86% of revenue.
AI Automation & Integration
Automation and AI integrations, mostly to modernize legacy systems, delivered in weeks from process discovery to production on several platforms. This is the fastest-growing line, led by a newer automation practice. Automations are chosen where the return can be measured.
Content Platforms & Training
Enterprise and web content management: software licenses, implementation and managed services, plus professional training.
The AI platform
The Company’s own AI software turns a client’s existing documents and systems into structured, reviewable plans for what to build, and it flags gaps and risks before anything is built. Everything sits in one shared model, so the output can be reviewed and checked for completeness, which a general-purpose AI chat tool does not do. Finished work flows to the client’s delivery tools.
Each enterprise deployment is kept separate, clients choose among leading AI models, including ones they host themselves, and client data stays under the client’s control. The platform is built to hold the largest enterprise programs.
Revenue up 63% and margin at a five-year high
A serviceable market of about $2B
Management’s forecast of $18.3M of revenue by 2030 sits inside the reachable range and includes no software revenue from the platform.
AI is increasing demand for product definition
Software build costs are falling
AI-assisted delivery is cutting the cost of building software by roughly 10x. Deciding what to build, and how the business behind it runs, has not become cheaper, so more programs now depend on that work being done well.
AI needs process models most companies lack
Most large enterprises now have an AI directive and a budget. Most still document how they operate in diagrams, documents and staff knowledge that AI cannot act on. Each AI program forces that material to be rebuilt as structured, machine-readable models, which is the work the Company’s teams and platform were built to do.
Large software platforms are active buyers
Enterprise-software platforms have paid $1.2B to $1.5B each for process-intelligence and adoption tools, which connect business strategy to working software. The Company offers services and a platform together at a much smaller size.
Investment highlights
Long tenure on Fortune 100 software programs
As AI lowers the cost of building software, the quality of the product definition decides whether a large program ships. The Company has done this work for many years on some of the largest programs its clients run. Its teams run clients’ internal systems the way a software company runs a product it sells.
Its AI software is already used on client work
Delivery teams already use the platform on client programs, and a Fortune 100 evaluation is underway. The go-to-market plan starts with pilots of two to five product managers that grow into team licenses. Target buyers, positioning, demo assets and an automated nurture program are built. The platform earns no revenue in the figures shown, so a buyer that sells it into its own client base adds a software line the business does not have today.
A documented way of working a buyer can scale
Years of enterprise programs are written into how the Company’s teams work. A buyer can teach and sell that approach across its own client base, and a competitor cannot reproduce it by hiring.
Long-standing Fortune 100 clients
The Company works inside Fortune 100 companies across several industries, several of them for more than a decade, and some engagements span multiple business units. These accounts have renewed through spending cycles, and a buyer inherits them as a base to sell into.
The same team defines and builds the system
In a single engagement the Company defines what to build, builds and automates the systems and supplies the platform. Other firms sell these capabilities separately. Product management leads every engagement, and no competitor offers the same combination.
Most of 2026 is already under contract
Signed contracts cover most of management’s 2026 revenue forecast, and the forecast through 2030 includes no standalone software revenue. A buyer with enterprise distribution can accelerate that growth.
Process and next steps
Transaction expectations
The founder owns the majority of the business with a small group of partners. There is no institutional capital, bank debt or litigation. Ownership is open to a full sale or a majority transaction with a strategic or financial partner that can scale the services business and take the AI platform to market as a product. The founder plans to stay focused on product and strategy through a transition.
Management and operations
Professional management runs the business day to day at market pay, so no owner-compensation adjustment is needed. The finance function is ready for diligence, add-backs total about 1.7% of revenue, and payroll, HR and IT are outsourced.
Indicative process
- Introductory call with the deal team to confirm strategic fit and transaction alignment
- Execution of a confidentiality agreement
- Distribution of the Confidential Information Memorandum and financial packet
- Submission of non-binding indications of interest
- Management introductions, letter of intent, and confirmatory due diligence
- Negotiation of terms and closing with the selected buyer
Talk to the deal team
Book a short introductory call using the calendar below, or fill out the form and a member of the team will reach out. Revenue Rocket is the exclusive advisor. Please send all questions through the deal team, reference Project Cobalt, and do not contact the Company.
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Book a 15-minute introductory call.
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