The integrated AI-native Go-To-Market operating group.
Five coordinated businesses, built around the orchestration layer of the modern revenue stack. Built for the decade that replaces the 2022 GTM playbook — assembled in months, not years. Decision-maker access, on the buyer’s invitation.
Earned through editorial intelligence senior buyers actually read, community senior buyers actually join, and a data contract that protects what they say in the room. Each surface compounds the invitation. The invitation is the moat.
“Every decade, the category consolidates around whoever owns the new strategic layer. This decade, that layer is Go-To-Market.”
The investment thesis, in a single sentence.
Companion documents
Two PDFs for readers who want to take the thesis with them.
The landing page is the living version. The two documents below are curated artifacts for deeper reading, sharing with colleagues, or diligence.
The essay
Bloomberg for B2B Go-To-Market
13 pages · ~8 minute read
The investment thesis argued through one analogy. Every layer Bloomberg owns in financial markets, Omnitech is building in revenue markets. Designed for a single read.
The operational argument. Market shift, $235B+ opportunity, the five-unit operating group, the closed-loop moat, competitive defensibility, and a roadmap of key milestones. Built in months, not years — the speed AI plus senior operators unlocks.
Go-To-Market is no longer a department. It is infrastructure.
For twenty years, Go-To-Market was a department. A team that ran marketing, sales, and revenue operations — downstream of product, downstream of engineering, downstream of finance. Something a company had, not something a company was built around.
In an AI-native stack, that has changed structurally. The modern B2B revenue architecture has five layers. Four of them are commoditising. The fifth is where the next decade of category value accrues.
History is a reliable guide.
Every decade, across industries, a new infrastructure layer emerges — and the companies that define that layer capture most of the category value it creates. This is not a pattern in technology. It is the pattern in how categories are built.
The pattern
Every decade, a new infrastructure layer emerges — and the companies that define that layer capture most of the category value it creates. Bloomberg for capital markets. Gartner for enterprise IT. Salesforce for cloud CRM. HubSpot for inbound marketing. Palantir for decision infrastructure. Stripe for payments. Snowflake for the modern data layer. Two operators — Foundry and Informa TechTarget — have publicly named the next $20B opportunity at the GTM layer, four years apart.
In each case, the pattern repeats: a layer that didn't exist as a category five years earlier becomes one of the most valuable layers in the stack. The companies that define those layers don't compete in a crowded category — they create the category other companies compete inside.
Go-To-Market infrastructure is the next. Omnitech Capital is building the operating group to define it.
The pattern, in real time· April 2026
The same shift is happening one layer below us.
The historical precedents above prove the pattern across decades. The same pattern is also playing out right now at the layer beneath GTM — the AI infrastructure layer — and the smartest infrastructure capital in the world is funding it.
On April 22, 2026, VAST Data closed a $1B Series F at a $30B valuation — backed by Nvidia, Drive Capital, Access Industries, Fidelity, and NEA, with $4B+ in cumulative bookings and $500M+ committed ARR. Customers include CoreWeave, xAI, JPMorgan Chase, Mistral, the U.S. Air Force, and Cursor. Founded in 2016, VAST set out to do something specific: collapse the fragmented AI infrastructure stack — storage, database, compute, agents — into a single integrated system. One platform, one data layer, one runtime. They call it the AI Operating System.
What VAST is building at the AI infrastructure layer is structurally identical to what Omnitech is building at the GTM layer. Same diagnosis — fragmentation. Same prescription — collapse the stack into an integrated system. Different domain.
2026 · AI Infrastructure
VAST Data
DataStorestorage layer
DataBasestructured data
DataEnginecompute & processing
AgentEngineexecution & agents
↓ collapsed into ↓
AI Operating System
same shape
2026 · Go-To-Market
Omnitech Capital
Signal layerpublications + community
Intelligence layerDecision-Maker Network
Execution layerENAI + IndustryGeniuses
Operator layerGTMBench fractional CxOs
↓ collapsed into ↓
GTM Operating System
“VAST is building the operating system for AI infrastructure. Omnitech is building the operating system for revenue.”
The same architectural move · one layer apart
Read the live brief
↗
Section 02 — The architecture
The modern B2B revenue stack has five layers.
The lower four layers are what most companies think of when they think “AI stack.” Data (ERP). Customer intelligence (CRM). Agentic AI. Foundation models. Each layer is getting more powerful every quarter. Each is also getting more commoditised every quarter — every vendor has access to the same CRM data, the same Claude API, the same agentic frameworks.
The differentiation is no longer who has the best model. The differentiation is who knows what to point the model at.
That question — what to point the model at — cannot be answered by any of the lower four layers. An LLM doesn’t know which market you should enter. An agentic AI doesn’t know which buyer segment is underserved this quarter. A CRM doesn’t know why its pipeline is decaying. Those answers live one layer above.
Without the GTM orchestration layer, the AI stack is a very fast engine with no destination.
An agentic layer without GTM context will generate outbound at scale — to the wrong accounts. A foundation model without GTM context will write perfect emails — with the wrong message. A CRM without GTM context will capture data — about buyers who were never going to convert.
The stack gets smarter every quarter. The results get worse every quarter. Because the layer that gives the stack direction is the layer most companies don’t have.
Section 03 — The market opportunity
The market that consolidates is already large.
The integrated Go-To-Market stack Omnitech is building addresses a layered market spanning sales technology, revenue operations, demand generation, B2B marketing, GTM talent, media and community, and enablement training. Each segment is large on its own. None is currently owned by a vertically integrated operating group.
$235B+ addressable today, projected to exceed $625B by 2030.
Five coordinated businesses, seven addressable segments, one integrated category. Every operating unit maps directly to one or more segments below.
Segment · Operating unit
Today
Projection
Sales Acceleration TechnologyENAI
$124.4B
$409.4B by 2033IMARC Group
CRM & Revenue OperationsENAI
$25.7B
$75.4B by 2029Gartner / Technavio
B2B Demand Generation ServicesIndustryGeniuses
$8.0B
$15.0B by 2033Strategic Revenue Insights
B2B Marketing SpendIndustryGeniuses + GTMplus
$18.9B
$30.8B by 2030Research and Markets
GTM Talent & Fractional ServicesGTM Bench
$14.2B
$25.9B by 2030Research and Markets
B2B Media, Events & CommunityGTMplus
$40.0B
$60.0B+ by 2030AMR / IAB / Statista
B2B Sales Enablement & TrainingGTM Institute
$5.7B
$11.8B by 2030Grand View Research
The segments are separately large. The structural winners will be the groups that serve them as one.
The table is not a collection of adjacent markets — it is the architecture of the group. ENAI anchors Sales Acceleration and RevOps. IndustryGeniuses captures B2B Demand Generation and a share of B2B Marketing Spend. GTM Bench owns the GTM Talent and fractional operator segment. GTMplus sits across B2B Media, Events, and Community. GTM Institute addresses the Sales Enablement and Training layer focusing on new AI roles such as GTM Operator, AI Prompt Engineer, AI-enabled AE, AI Content Orchestrator, and AI RevOps Specialist etc. The investment thesis is that the next decade rewards the operating groups that integrate across them. Omnitech is building for that integration.
Section 04 — The future of Go-To-Market
Go-To-Market is becoming the operating system for commercial growth.
The current Go-To-Market category — the $235B+ that consolidates across the seven segments above — is itself in the process of expanding. AI applied to industry workflows is collapsing categories that ran in parallel for forty years. Advisory work, software implementation services, departmental operating budgets, and the GTM stack itself are converging into a single operating layer.
What was once sold as strategy decks and software implementation is being replaced by vertically focused AI agents that do the tasks. What used to be measured as Finance, Customer Service, HR, Operations, Logistics, or Legal output is increasingly measured against revenue contribution — because once routine work is performed by agents, the remaining human work re-anchors upstream to a single question: how does this create commercial growth?
Go-To-Market stops being a department. It becomes the operating system the entire enterprise runs on.
Figure 01 — The structural shift
Old vs New Go-To-Market — seven dimensions, one shift.
Omnitech is the integrated operating group purpose-built for the right column of this shift.
The expanding category
From a $235B category today to a much larger operating layer as the convergence completes.
Same seven segments, organic growth, plus early AI-agent revenue. The opportunity from the table above.
$625B+
2030+ · thesis projection
The operating system for commercial growth
GTM absorbs the advisory layer (consulting, analyst research, software implementation) and the function-level revenue impact of Finance, Customer Service, HR, Operations, Logistics, and Legal.
$1.5T+
Methodology note · the $1.5T+ figure. Internal Omnitech thesis projection, not a single sourced number. Built from published 2026 category sizes: global management consulting (~$1.11T, Research and Markets / Mordor Intelligence), B2B sales technology and outsourcing (~$127B, Business Research Insights / Fortune Business Insights), and agentic AI / AI agents (~$12B, Fortune Business Insights). These categories overlap and the sum carries forward expected organic growth to 2030+ plus projected function-level revenue absorption as agents replace routine departmental work. It is a directional estimate of the addressable surface area as the convergence completes, not a sourced market-research figure.
How every function routes to revenue
When agents perform the routine work, human work re-anchors upstream.
Operational efficiency tied to revenue — not abstract KPIs
Finance
From closing the books to unit economics that drive pricing decisions.
Customer service
From resolving tickets to expansion signals and retention drivers.
HR
From headcount management to revenue per employee and capacity planning.
Operations
From process compliance to throughput that compounds into commercial capacity.
Logistics
From shipment tracking to on-time delivery as a renewal driver.
Legal
From contract review to deal velocity and revenue recognition timing.
Omnitech is positioned for both the category as it stands today — the $235B+ that consolidates across the seven segments — and the operating system it is becoming.
Section 05 — The token economy & AI-native industry
The rise of the token economy and AI-native industry.
The integration thesis is larger than the GTM category alone. Step back from the GTM stack and look at where commercial growth sits in the AI economy. The full chain runs from compute to GDP — and tokens, the unit of inference performed by digital workers, are the new economic primitive flowing through every link.
Jensen Huang's chain — compute → tokens → intelligence → digital workers → revenue → GDP — compresses two distinct stages into a single “Revenue” link. Unpack it, and the operating layer becomes visible: Industry GTM is where revenue is actually captured — the catalyst. Industry Transformation is where that revenue aggregates into sector-level change — the structural outcome.
Figure 02 — The economic chain, unpacked
From compute to GDP — and the layer where revenue is captured.
Industry GTM is the value-capture node Jensen's chain compresses into “Revenue.” Industry Transformation is the structural outcome — sectors rebuilt around AI labour — that the chain stops short of naming. Both layers are where Omnitech operates.
What does this mean for the advisory layer specifically? The shift that reshapes software-implementation firms is the same shift that produces a new layer of AI-native industries — hospitals, retailers, manufacturers, financial services, logistics — all built around AI workforces orchestrated by partners, not implemented by consultants.
Figure 03 — The advisory shift
Old vs New Advisory Firms — from implementers to orchestrators.
Software implementation firms become AI workforce orchestrators. The industries they serve become AI-native. This AI-Native Industries layer — the bottom band of the diagram — is exactly where IndustryGeniuses is now positioned.
Operating group response · IndustryGeniuses expansion
IndustryGeniuses now deploys AI agents across industry verticals — not just B2B revenue.
As the operating system for commercial growth absorbs the function-level work of every vertical, IndustryGeniuses is broadening from B2B demand generation execution into AI agents and digital labor deployed across industry verticals. The unit's mandate now matches the structural opportunity: every vertical needs the AI workforce, and every vertical's workflows ultimately route back to revenue.
Financial services
Healthcare & life sciences
Logistics & supply chain
Manufacturing
Legal & professional services
Retail & consumer
Construction & built environment
Education & training
Same operating group. Same integration thesis. A larger surface area — one that matches the size of the operating system Go-To-Market is becoming.
The token economy creates value at two layers — Industry GTM and Industry Transformation. The advisory firms of the previous era become the AI-workforce orchestrators of the next. Omnitech operates at both layers — the GTM operating system and the AI-native industry layer. The convergence is now visible.
Section 06 — The operating group
Five businesses. One coordinated strategy.
Omnitech Capital operates five coordinated businesses across the full Go-To-Market orchestration layer. Each is a standalone brand with its own customers, product, and economics. Together, they form the integrated operating group the category is moving toward.
AI-native sales intelligence and engagement software. Built AI-first from the ground up — not AI bolted onto a legacy sales engagement tool. Signals, workflows, and automation across outbound, pipeline, and RevOps, built for how revenue teams actually work in the age of AI.
Senior fractional Go-To-Market operators — Director to CxO — deployed into B2B companies at the growth inflection. All four GTM disciplines: RevOps, Demand Generation, Marketing, Sales. Plus Industry Advisors with deep sector expertise. Operators who’ve led GTM at Salesforce, Google, AWS, McKinsey, Deloitte, PepsiCo, and Nestlé.
The execution agency for B2B companies that need real pipeline, not creative awards. Demand generation, ABM, content, and campaign execution — run by practitioners, measured against revenue outcomes, not vanity metrics.
04
The Publications
Live + In build
Three editorial properties covering different tiers of the revenue decision chain. GTM Bench Review (live, weekly) for GTM practitioners. BoardroomAI (in build) for board directors and C-suite. VerticalAI (in build) for industry leaders. One editorial operation. Three audiences. A proprietary buyer-signal network covering verticals and decision-makers.
The customer-facing platform that unifies the portfolio. GTMplus directly operates the community and training layer — an open practitioner community, the VP+ Inner Circle with preferential commercial economics across the platform, GTMInstitute training, and GTM Summit London. Publications, software, operators, and agency all integrate through GTMplus.
Section 07 — Why this structure is defensible
Integration is not a pitch. It is the moat.
Most Go-To-Market platforms are tool stacks bolted together through acquisition. Most Go-To-Market agencies don’t own proprietary media. Most Go-To-Market publications don’t have operator practices underneath them.
Omnitech Capital owns all three layers, built from the same thesis, under one coordinated group.
01
The publications generate buyer-signal data at the source.
Our editorial properties cover industry verticals and C-suite decision-makers directly. The intent signals flowing through our network inform what we publish — and what our operators deploy into client engagements — before the market catches up.
02
The operators interpret the signals into strategy.
The same senior GTM operators on our Bench contribute to our publications. Which means when a fractional CRO deploys into a client, they arrive with the context our editorial team has already compiled. The strategic onramp collapses from months to days.
03
The software and agency execute the strategy into pipeline.
ENAI is the AI-native execution layer. IndustryGeniuses is the agency delivery arm. Both ship the campaigns, workflows, and signals our operators and publications identified upstream. No handoff friction because there is no handoff.
04
The community compounds the whole.
GTMplus members receive preferential economics across the platform — turning single-product buyers into multi-product accounts, and turning customers into peer evangelists. Account LTV grows with every additional unit touched.
And tenure compounds the switching cost. Configured workflows, peer relationships, published contributions, tenure-weighted standing inside the VP+ Inner Circle — none of it travels. Cancelling the subscription is easy. Replacing what was built inside it is not.
This is not a flywheel diagram. It is the orchestration layer for modern revenue infrastructure.
The SpaceX precedent · A structural pattern from outside B2B
Vertical integration is what defines the next category-leading operating group. SpaceX is the precedent.
SpaceX builds the rocket, the engines, the avionics, and operates the launches. Starlink — the global communications layer the rest of the ecosystem runs on — sits on top. Tesla, Optimus, xAI, X Corp, Neuralink, and The Boring Co. all run on the same vertically integrated infrastructure and engineering culture. The integration is not a side effect of common ownership — it is the design. Cost-per-kilogram collapsed 25x. The platform is structurally uncompetable.
Most companies in B2B Go-To-Market are a stack of vendors — a CRM, plus an intent-data provider, plus a martech agency, plus a community platform, plus a training company. Omnitech operates the integrated stack as one group — and owns the decision-maker layer (BoardroomAI, VerticalAI, GTM Bench Review, VP+ Inner Circle) that the rest of the stack runs on. Same architectural pattern, applied to a different category. The integration is the moat.
The case above, argued in full. What ZoomInfo and SciLeads teach us about defending B2B intelligence businesses in the age of agentic AI — and why, in 2026, anything that looks like a database loses and anything that looks like a network, a point of view, or earned judgment wins. Three-stage pattern, six-row moat taxonomy, portfolio flywheel analysis, and ninety-day priorities.
Publications and the GTMplus community capture buyer signal at the source. GTM Bench operators translate it into strategy. ENAI and IndustryGeniuses execute into pipeline. Execution generates new proprietary data. Editorial and GTM Institute training close the loop — compounding the advantage with every iteration.
01
Publications · GTMplus community
Signals at the source.
Intent, seniority, industry, and topic engagement data from GTM Bench Review, BoardroomAI, VerticalAI, and the GTMplus community + events — captured before the market catches up.
↓
02
Operators · GTM Bench
Signals into strategy.
GTM Bench operators translate editorial and platform signal into market-entry, segmentation, and positioning decisions for client engagements.
↓
03
ENAI · IndustryGeniuses
Strategy into pipeline.
ENAI and IndustryGeniuses deploy the strategy as campaigns, outbound sequences, and account plays — at operator-directed granularity.
↓
04
Execution · First-party signal
New proprietary data.
What converts, what doesn’t, which messages land, which accounts respond — all captured as first-party signal, not licensed intent.
↓
05
Feedback · GTMplus training
Data back into the system.
Conversion data shapes editorial. Editorial and execution insight feed GTM Institute training — and sharpen every operator engagement after.
OUTCOME
Compounding advantage.
↩ The loop closes — back to 01 · Signals at the source
The more the platform runs, the smarter it gets. Compounding advantage — not from a single product, but from the architecture itself.
Section 08 — The open conversation
The next step is a conversation.
This page is an invitation, not a pitch. We’re building a thesis-stage operating group, and we have specific conversations we want to open: with investors for whom integrated operating groups are a deliberate thesis, with strategic partners who see the same category shift, and with operators who want to help build the next decade of Go-To-Market — not defend the last one.
If any of that resonates, there are two ways to start.
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