The Company Mapping the Invisible Software Inside 40 Million Businesses

Somewhere inside a company you have never visited, a database is humming, a cloud contract is nearing renewal and a hiring manager has typed the name of an obscure software tool into a job description. To most readers, these are unrelated scraps. To HG Insights, they are coordinates. The Santa Barbara company gathers signals like these and turns them into a commercial map for businesses that sell technology to other businesses.

The map is meant to answer questions that sound simple until a sales organization tries to agree on them. How large is our real market? Which accounts fit our product? Who already uses a rival? Where is spending likely to grow? Which buyers are researching a category now? A strategy team may buy an analyst report, marketing may run an intent platform, sales may search a contact database and operations may maintain a different truth in the CRM. HG’s pitch is that the clues become more useful when they resolve to the same company, location and buying center.

That proposition has carried the business from its 2010 origins as HG Data into a broader category it calls Revenue Growth Intelligence. The current product combines a data fabric with analytical software, predictive models, seller guidance and tools for building AI agents. It is less a shiny list of leads than a continuously revised argument about where revenue might come from.

01 / The raw materialThe tell in the job post

Technographics - evidence about the software, hardware and cloud services a company uses - remain HG’s most recognizable ingredient. Some technologies announce themselves on a public website. The harder detections live behind the firewall. HG says it applies machine learning and proprietary methods to public documents such as job postings, company materials and contracts, then links those mentions to products, vendors, locations and corporate entities. A request for a Kubernetes engineer, for example, is not merely a vacancy. It may be evidence of an installed environment, a technical direction and a buying center.

No single clue is conclusive. A product name may describe a current deployment, a migration target or a skill the employer hopes to acquire. This is why context and entity resolution matter. HG’s first patent, granted in 2024, covers methods for analyzing clusters of online documents to predict changes including technology adoption, company growth and workforce shifts. The company’s data work is essentially a long exercise in turning ambiguous language into structured evidence.

The resulting Revenue Growth Intelligence Fabric spans firmographics, technology installs, IT and AI spending estimates, cloud consumption, contracts, corporate hierarchies, buying centers, topic mentions, buyer intent and verified contacts. HG reports more than 40 million company profiles in the Fabric, along with billions of source records. Those figures describe coverage, not certainty. The practical value comes from comparing imperfect signals rather than treating any one field as gospel.

“For most sales organizations, the finite resource is time.”BCG, in an HG partner presentation

02 / The useful inversionBuild the market from the accounts up

Traditional market research usually begins at altitude: a category will be worth a certain number of billions, growing at a certain rate. HG takes the opposite route. Its Market Analyzer lets a company define an ideal customer, inspect matching accounts and roll them upward into total, serviceable and obtainable markets. A cybersecurity vendor can narrow a market by geography, company size, installed infrastructure, maturity, estimated spend or the presence of a competitor. The output is not only a market number; it is the list of businesses underneath it.

This bottom-up structure is particularly useful for territory planning, account-based marketing and competitive displacement. A sales leader can assign territories against measured opportunity rather than last year’s map. A marketer can build a segment of accounts with a rival product and a plausible contract window. A product executive can examine where a category is gaining or losing installed presence. The same data supports a board-level market argument and a rep-level call list, which is a quietly important form of organizational alignment.

03 / The customerFor companies that sell the expensive, complicated stuff

HG is built for B2B technology sellers with long buying cycles, multiple decision makers and products whose relevance depends on the customer’s existing environment. Publicly displayed customer logos include IBM, Cisco, Hewlett Packard Enterprise, NetApp and Equinix. HG says its products are trusted by 90 percent of Fortune 500 technology companies. Its customer stories also reach into growth-stage software: HR platform HiBob used HG alongside ZoomInfo to gain a more complete global view of its market.

Different users enter through different doors. Corporate strategy and finance teams use market sizing. Product marketers watch categories and competitors. Marketing and RevOps teams refine ideal-customer profiles, score accounts and enrich records. Sellers want research briefs, contact recommendations and a reason to call today. Data and AI teams can license the Fabric through APIs, Amazon S3, warehouses and the company’s MCP-based agent tools. HG is designed to sit beside systems such as Salesforce, HubSpot and Gong, not demand that customers replace the stack around it.

04 / The deal logicThree acquisitions, three missing pieces

The shape of the present company is easiest to see through its acquisitions. Intricately, bought in 2022, added cloud product adoption, consumption and spend signals. TrustRadius, acquired in June 2025, added a community of technology buyers, verified product reviews and direct evidence that people were researching a vendor, rival or category. MadKudu followed in August with predictive scoring and tools that translate signals into operational sales guidance.

Together, the deals close a loop: understand the market, identify a fitting account, detect movement, find the people involved and recommend a play. TrustRadius also gives HG a customer-facing media asset. Reviews can improve a vendor’s product page and campaigns while the research behavior behind them becomes a signal for targeting. It is a neat two-sided arrangement, though buyers and sellers will naturally care about clear privacy boundaries and the difference between an opted-in lead and anonymous market activity.

05 / The distinctionNot another phone book with a dashboard

HG operates in an unruly neighborhood. ZoomInfo and Apollo are synonymous with contacts and prospecting. 6sense and Demandbase orchestrate account-based programs and intent. Bombora supplies intent data. BuiltWith and Datanyze detect web technologies. Gartner, IDC, Forrester and GlobalData sell market research. A sufficiently determined enterprise can assemble parts of all of this in a warehouse.

HG’s defense is resolution and intersection. Its technographics aim to reach beyond website tags into harder-to-see enterprise deployments. Spending forecasts, contract details, parent-child hierarchies, location and buying-center context help explain the commercial meaning of an install. Intent from different sources adds timing. Contacts add a person. The shared HG Company ID is the humble mechanism holding the picture together.

That distinction also clarifies where HG fits. It is strongest when the product being sold is expensive enough, the market complicated enough and the account universe valuable enough to justify deep enrichment. A local service business does not need a forecast of AI infrastructure spend. A global cloud, cybersecurity or enterprise-software vendor may consider that context central to territory design and competitive strategy.

06 / The new interfaceFrom dashboard to coworker

In March 2026, HG introduced a unified Revenue Growth Intelligence Platform. Market Analyzer handles market structure and ideal-customer analysis. Data Studio lets operations teams build predictive account, lead and product-qualified-lead models without code. Sales Copilot turns signals into daily briefs, automated research, contact suggestions and personalized plays. RGI Agent Builder gives developers MCP tools for constructing their own agents on the Fabric.

The shift matters because sales intelligence has long suffered from the “interesting dashboard” problem. An analyst explores it; everyone else returns to the CRM. HG’s agents are an attempt to deliver a small, contextual answer where work already happens: this account fits, its signals changed, these contacts matter, here is the competitive angle. The interface becomes less about browsing a database and more about interrogating it.

“The answer can’t be just spending on more tools, data, and dashboards.”Rohini Kasturi, chief executive officer

07 / The businessA private data company growing by subscription and scope

HG Insights is a Delaware corporation headquartered in Santa Barbara. Craig Harris launched the company with a founding group that included Tracy York, who remains VP of Product for the RGI Fabric. The company raised a $12 million Series B in 2016 and received a significant, undisclosed growth investment from Riverwood Capital in 2021. It has not published a valuation. Inc. listed HG with 51 to 200 employees in its 2024 profile and named it to the Inc. 5000 for a third consecutive year.

The business model is enterprise subscription and data licensing. Customers can buy the SaaS platform, direct access to the Fabric, intent-driven leads, Customer Voice services and agent infrastructure in modules or combinations. HG says Platform and Fabric pricing depends on consumption; larger agreements vary by data volume, capabilities, users, integrations and implementation. That makes the company economically closer to an enterprise data supplier than a self-serve sales app.

Its culture language emphasizes accountability, inclusion, collaboration and shared ownership. A more tangible artifact is the annual Santa Barbara hackathon, where teams prototype data products. The practice fits the company’s character: the clever part is rarely a grand reveal. It is someone finding a more reliable way to connect a strange little clue to the right company.

08 / What happens nextThe map gets an opinion

HG’s opportunity is to become the context layer beneath an enterprise’s go-to-market AI. If every copilot needs clean company identities, current account signals and permissioned internal data, the Fabric can travel farther than HG’s own interface. Its risk is familiar to every data vendor adopting generative AI: agents are only as trustworthy as the evidence, matching and explanations underneath them. A confident recommendation attached to a stale install is worse than a cautious filter.

Still, the underlying idea has aged well. Businesses constantly reveal themselves in fragments. They hire for one stack, spend into another, research a replacement and leave a trail across documents, systems and communities. HG Insights makes those fragments legible to the people deciding where to place a sales team’s next hour. In a market crowded with names, numbers and notifications, the useful product is not more noise. It is a map that can show its work.