HG Insights Launches Contextual Intelligence Platform
Contextual Intelligence Platform gives GTM teams and AI agents a unified, connected picture of markets, accounts, and buyers to compete, win, and grow with precision.
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HG Insights has launched the Contextual Intelligence Platform, closing the context gap that leaves autonomous AI agents confidently acting on fragmented, isolated data.
By giving GTM teams and agents one unified, connected picture of markets, accounts, and buyers, grounded in decision-ready intelligence, it lets them compete, win, and grow pipeline and revenue faster.
The launch also marks a new chapter for HG Insights’ brand, with its integrated platform debuting alongside a refreshed identity that reflects where the company and the market are headed.
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“Every GTM team is adding the same agents, the same tools, the same playbooks. When the infrastructure is equal, whoever knows the account best wins,” said Rohini Kasturi, CEO of HG Insights.
“Most vendors still sell disconnected data and call it intelligence. We’ve built the intelligence layer for autonomous, agentic GTM. Our platform connects the data, gives it context, and derives decision-ready signals that power teams and AI agents to execute with precision.”
AI agents are now table stakes in enterprise GTM. The differentiator is the completeness, depth, and context of the intelligence behind them.
Most AI agents working in GTM draw on isolated, fragmented internal and commodity datasets that lack the entity resolution and context required for accurate interpretation.
The same company is able to show up as multiple accounts, and a subsidiary’s spend would therefore be missed or double-counted under the wrong parent. An intent signal from an account that already owns the product could be flagged as new business instead of an expansion, and one from a competitive account can be chased as winnable.
Marketing and sales are able to rely on job titles rather than evidence of who owns the product. Without that context, an agent returns a fast, confident answer that is fundamentally wrong. As more GTM work gets automated, those errors scale.
HG’s Contextual Intelligence solves this problem by connecting technology installations and usage, spending, buyer intent, buying centres, and contacts to an account and its corporate hierarchy. It tracks changes over time and computes new signals that no individual data source can provide.
This gives teams and AI agents the context, combined with a customer’s first-party data, to distinguish opportunities, prioritise accounts and leads, and guide GTM execution with precision.
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“Account data still lives across a dozen separate systems inside most organisations, and that fragmentation matters even more as agentic autonomy increases and agents become embedded within GTM workflows,” said Michael Levy, analyst at GZ Consulting.
“Accurate account and contact resolution, combined with a comprehensive buyer context, determines whether an agent can reason effectively and take actions that drive pipeline growth. Contextual intelligence will drive GTM outcomes and deliver compounding value as the agents and applications on top of it evolve.”
What’s new in the Contextual Intelligence platform:
- Fabric, the data and intelligence foundation of the platform, has expanded its company, technology, and spend coverage and now includes funding and M&A intelligence, automatic hierarchy updates, and contacts matched to the buying centres that own a given technology.
A new Momentum signal has been added that shows whether a vendor, a portfolio, or a product is gaining or losing ground. Each of these additions helps GTM teams and agents make more precise GTM decisions.
A declining footprint, spend, and intent can flag a competitive displacement opportunity, while growth across all three shows a competitor gaining ground. Fabric can be licensed on its own and delivered by API or Direct Feed into a customer’s data warehouse, CRM, applications, or models.
- HG Copilots, including Market Analyzer, Data Studio, and Sales Copilot, help GTM teams assess markets, optimise coverage, target accounts, build audiences, and engage buyers. Sales Copilot now tailors its guidance around each customer’s own products, buyers, and sales motions.
A rep opens a ranked account list with research, engagement history and intent signals, suggested sales play, product pitch, and buyer committee contacts, all with clear reasoning. That same transparency now extends to predictive AI scoring across HG Copilots.
Unlike black-box scoring, Fit, Need, and Intent models update dynamically to sharpen lead and account prioritisation while staying deterministic, explainable, and adjustable.
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- HG Agents automate time-consuming GTM tasks such as expansion sizing, territory coverage, account research, signal monitoring, brief and outreach drafting, and enrichment that used to take hours of manual data gathering, mapping, and analysis.
HG Agents are reachable from Slack, Microsoft Teams, the HG interface, or embedded directly into a customer’s own application using standard Model Context Protocol (MCP). A new HGSuperagent interprets user requests, selects the right specialist agents, and assembles the result with every claim cite-sourced, so a user never has to know which agent to call.
An account research brief can return over 30 data points within 90 seconds. A team that once had time for only its priority accounts can now cover an entire territory.
- HG MCP Server gives customers’ AI agents and applications direct access to HG’s contextual intelligence without requiring them to first build a separate data infrastructure.
Through one secure, governed connection, they can query market, account, and buyer intelligence alongside TrustRadius product reviews, SEC filings, federal contract data, and other live web research.
They can also draw on a growing library of curated workflows, trigger and monitor HG Agents, and query the Fabric for custom analysis, market sizing, ICP segmentation, ABM, and campaign design. Every result traces back to its source data, so users and agents can verify what’s behind their GTM decisions.
- Customer Voice, powered by TrustRadius, further extends the platform. As previously announced, it feeds the Fabric with downstream buyer-intent signals from a community of over 12M technology buyers actively researching products.
It also accelerates the collection of customer-verified, in-depth reviews and ratings for social proof, SEO, and AI citeability, plus GEO monitoring to track how vendors show up across AI search.
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Expanding the AI Ecosystem
HG Insights extends Contextual Intelligence across the enterprise AI ecosystem, so customers do not have to move their data, rebuild workflows, or standardise on one AI platform to use it.
Fabric, HG Copilots, and HG MCP Server are available through AWS Marketplace, which simplifies procurement and lets eligible customers apply existing cloud commitments toward HG Insights. HG MCP Server brings the same intelligence into Amazon Quick, Anthropic, OpenAI, and Microsoft.
Enterprises run multiple models, agents, and AI platforms, and the interface varies by team. The GTM intelligence behind those experiences does not have to vary. HG separates the intelligence layer from the interface, so an analyst in Microsoft, a GTM engineering team building with OpenAI, and a rep in an HG Copilot all work from the same picture of markets, accounts, and buyers.
