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HG Insights has launched its Contextual Intelligence Platform, designed to give go-to-market teams and AI agents a single view of accounts, markets and buyers.
The launch brings new tools across the company's data, copilot and agent products, including a new Superagent, explainable scoring models, a Momentum signal and an MCP Server for governed access from customers' own AI systems.
HG Insights is targeting marketing, sales and customer success teams that are increasingly using AI agents for account research, lead prioritisation and outreach. It says these tools often rely on fragmented internal and third-party datasets, creating errors when account hierarchies, installed technologies, spending data and buyer intent are not connected.
The new platform is intended to address that by linking technology installations and usage, spending, buyer intent, buying centres and contacts to specific accounts and their broader corporate structures. It also tracks changes over time and generates combined signals from those sources.
One of the headline additions is HG Superagent, an orchestration layer that takes requests in plain language, selects specialist agents and assembles a response with source citations. The company says this is meant to spare users from having to choose which agent to use for a particular task.
Another change is to the company's Fit, Need and Intent scoring models. According to HG Insights, the models are now deterministic, explainable and adjustable rather than operating as black boxes, allowing customers to inspect and modify how scores are generated.
The company says this addresses a broader issue in business sales software, where trust in AI-driven recommendations has been weakened by opaque models. The scoring changes apply across its HG Copilots products, including Market Analyser, Data Studio and Sales Copilot.
Sales Copilot has also been updated to tailor guidance around a customer's own products, buyers and sales motions. HG Insights says a sales representative can open a ranked account list showing research, engagement history, intent signals, suggested sales plays, product pitch guidance and buyer committee contacts, alongside the reasoning behind the recommendations.
Combined signals
The platform's Fabric data layer has also been expanded. It now includes broader company, technology and spending coverage, along with funding and mergers and acquisitions intelligence, automatic hierarchy updates and contacts matched to the buying centres responsible for specific technologies.
Fabric also adds a new Momentum signal. Instead of treating technology footprint, spending and buyer intent as separate indicators, the platform combines them into a single measure intended to show whether a vendor, portfolio or product is gaining or losing ground within an account.
HG Insights says this can be used, for example, to identify competitive displacement opportunities when footprint, spending and intent are all declining. By contrast, growth across all three categories may indicate that a competitor is strengthening its position.
Fabric can also be licensed separately and delivered by application programming interface or direct feed into a customer's data warehouse, customer relationship management system, internal applications or models.
Open access
Another part of the launch is HG MCP Server, which gives customers' own AI agents and applications direct access to HG data through a governed connection. The server is designed to let customers query market, account and buyer intelligence without moving to a single AI platform or first building separate data infrastructure.
The product supports external agents built on systems such as ChatGPT and Claude, reflecting demand from companies running multiple AI models and interfaces across different teams. HG Insights says the aim is to separate the intelligence layer from the user interface so the same underlying account and market view can be used across different environments.
According to the company, results returned through the MCP Server trace back to source data. It says the server can also provide access to a library of workflows, trigger HG Agents and support custom analysis for areas such as market sizing, ideal customer profile segmentation, account-based marketing and campaign design.
Rohini Kasturi, Chief Executive Officer of HG Insights, said the product was built to address the limits of disconnected data in automated go-to-market work. "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 Kasturi. "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."
Michael Levy, Analyst at GZ Consulting, said the quality of account resolution and buyer context would become more important as AI agents take on more tasks inside revenue teams. "Account data still lives across a dozen separate systems inside most organizations, and that fragmentation matters even more as agentic autonomy increases and agents become embedded within GTM workflows. Accurate account and contact resolution, combined with 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," said Levy.
HG Insights says the platform is available on a consumption-based pricing model using Intelligence Credits, with HG Copilot modules starting at USD $22,000.