What is Context Enrich?

Context Enrich gives the AI you build buyer context no LLM has: personality predictions from Humantic AI’s proprietary model, research from harnesses purpose-built for GTM, and account and people signals, through the API and MCP.

Who is Context Enrich for?

Teams building their own AI agents, apps or context graphs for GTM, such as GTM engineering, RevOps and product teams.

Why not just use an LLM for buyer context?

Every team can ask the same LLM, so its context does not set you apart, and on personality it stays at 65 to 70% accuracy. Humantic AI’s proprietary model reads each buyer with 87%+ accuracy.

How does it fit into a context graph?

Your internal data and the external data you subscribe to stay where they are. Context Enrich adds the buyer layer: people, accounts, signals, visitors and intent, from People Research Agent, Account Research Agent, Buyer Signals, Visitor ID and Intent Scoring.

Which other Humantic AI products work with Context Enrich?

Context Enrich works with the other 7 Humantic AI products on one Buyer Intelligence platform: Account Research Agent (Account Intelligence) researches the account; People Research Agent (People Intelligence) profiles each buyer; HumanMail Agent writes new emails and replies for the buyer; Visitor ID (Visitor Intelligence) identifies who is on your website; Intent Scoring (Intent Intelligence) shows which accounts are in market; Buyer Signals give account and people signals and keep an Account Research Agent report current on your schedule; and Data Streams are live data pipelines for jobs, tech stack changes and website visitors. Humantic AI runs on 3 surfaces, the web app, the API and MCP, and Kairos, the activation engine, puts every product inside the tools your team already uses.

Book a demo

Context Enrich: Unique Buyer Context

Building your own AI? Give it context no LLM has, from our proprietary AI model and GTM harnesses.

Start free trial

Free for 7 days. No credit card.

The buyer context your AI agent gets through MCP or the API for Megan Reyes, VP Revenue Operations at Walmart: how she decides (Dominant, Influential, shown as style bars), lead with data and ask for 15 minutes, and a live signal that Walmart is researching sales coaching. Below, the personality read holds up 87%+ with the Humantic AI model against 65 to 70% for a general LLM.

Context You Can’t Get Anywhere Else

Not the same LLM everyone uses.

A Proprietary AI Model

Personality prediction builds a profile of every buyer: context you don’t get anywhere else

Purpose-Built Harnesses

Account and people research harnesses make sure every piece of context is reliable and trustworthy

Signals Built For Tech Selling

Ongoing account and people signals from public and private data, hard to track any other way

Private Data Sets

Stakeholder, intent, hiring and tech stack data that general models never see

“Much more comprehensive than ChatGPT or others”

Mark FoleyVP Global Accounts, Sandler

Build A Context Graph That Is Actually Differentiated

Everyone’s context is unique. Unique is not differentiated.

Your own data

CRMSlackEmailCallsDocs

Yours, and essential.
Data you subscribe to, and LLMs

Data providersWeb dataGeneral LLMs

Anyone can buy the same data and ask the same LLM.
Humantic AI

PeopleAccountsBuyer SignalsVisitorsIntent

A proprietary model and purpose-built harnesses: context others do not have.

Your context graph

Your agents now know how each buyer decides

Your AI agents and apps

See Context Enrich In Action

Ask in Claude: it calls Humantic AI through MCP and answers with buyer context.

The same buyer context reaches the agents and apps you build, through MCP and the API.

Start free trial

Walmart account brief for Snowflake ⌄Share

Using the Humantic AI connector, open my existing Walmart account report (seller: Snowflake). Give me Walmart’s top 3 priorities and the economic buyer, in a short brief I can read before a first call.

Used Humantic AI integration, loaded tools ›

Here’s your pre-call brief from the Walmart report (Snowflake as seller, generated Nov 3, 2026).

Framing: Walmart.com sits inside Walmart U.S. and has no separate P&L, so tie any business case to Walmart U.S. operating income.

Top 3 priorities

Digital spend has to prove its return. Every project faces a hard return bar. Angle: faster time to insight, quicker proof of payback.
Omnichannel execution now drives U.S. growth. eCommerce added about 4.3 points of comparable sales growth. Angle: one live data layer across store and web.
AI search and agent-led shopping are now named risks. Angle: governed AI with fast testing and guardrails.

Economic buyer: James Carter, CFO. His goals are protecting operating margin and getting stronger ROI proof for tech spend. Lead with payback, not features.

Other roles in the buying group:

Megan Reyes, Chief Growth Officer: the champion.
Anika Rao, CTO of Walmart U.S.: the technical buyer.

+Write a message…

Ask in ClaudeWith the Humantic AI connector
Claude calls Humantic AIAnd opens your Walmart report
An answer with buyer contextPriorities, the buyer and the roles

What Customers Say About Context Enrich

“To me, it’s a must-have tool.”

Clint BabcockVice President

Watch the video story

“…this tool has helped our sales team tremendously…”

Vendy PetersenSales Manager, North America

See Context Enrich on your own deals.

Start free trial Book a demo

For GTM Engineers And AI Developers

Use both: MCP for AI assistants and agents, the API for your own product. MCP details · API details

Building your own AI agent?

What an AI agent has on its own, and with Humantic AI over MCP
Context	Your agent today	With Humantic AI
Data	Yes	Yes
Web search	Yes	Yes
How each buyer decides	No	Yes
What the account cares about	No	Yes

Building into your own product instead? Use the API.

The request

# Create a profile from a LinkedIn URL
curl "https://api.humantic.ai/v1/user-profile/create?apikey=YOUR_API_KEY&id=https://www.linkedin.com/in/their-profile/"

# Fetch it with the same id
curl "https://api.humantic.ai/v1/user-profile?apikey=YOUR_API_KEY&id=https://www.linkedin.com/in/their-profile/&persona=sales"

The response carries

Top-level fields in a Humantic AI profile response, and what each one means
Field	What it means
`personality_analysis`	DISC and Big Five (OCEAN) scores
`persona`	what to say, what to avoid, key traits
`metadata`	confidence score and status
`usage_stats`	your quota used

Authentication: One API key on every call; keep it on your server. Get one in the docs with a 21-day free trial, no card needed.
Examples: Plain HTTPS from any language. The docs have cURL, Python, JavaScript and httpie samples and a Postman collection.
Async and errors: A create call can return IN_PROGRESS (status 21): fetch again with the same id after 15 seconds. Below 20 is success, 20 to 40 in progress, above 40 a failure.
Rate limits: A warning email first, then a 30 minute block only past the hard limit. Read the limits
Security: SOC 2 Type 2 audited and GDPR compliant. People who opt out are never analyzed, and you can exclude regions. Visit the Trust Center
Pricing: Credits go only on processed reports, and a repeat fetch in the same month counts once. See pricing

FAQs

Context Enrich gives the AI you build buyer context no LLM has: personality predictions from Humantic AI’s proprietary model, research from harnesses purpose-built for GTM, and account and people signals, through the API and MCP.
Teams building their own AI agents, apps or context graphs for GTM, such as GTM engineering, RevOps and product teams.
Every team can ask the same LLM, so its context does not set you apart, and on personality it stays at 65 to 70% accuracy. Humantic AI’s proprietary model reads each buyer with 87%+ accuracy.
Your internal data and the external data you subscribe to stay where they are. Context Enrich adds the buyer layer: people, accounts, signals, visitors and intent, from People Research Agent, Account Research Agent, Buyer Signals, Visitor ID and Intent Scoring.
Context Enrich works with the other 7 Humantic AI products on one Buyer Intelligence platform: Account Research Agent (Account Intelligence) researches the account; People Research Agent (People Intelligence) profiles each buyer; HumanMail Agent writes new emails and replies for the buyer; Visitor ID (Visitor Intelligence) identifies who is on your website; Intent Scoring (Intent Intelligence) shows which accounts are in market; Buyer Signals give account and people signals and keep an Account Research Agent report current on your schedule; and Data Streams are live data pipelines for jobs, tech stack changes and website visitors. Humantic AI runs on 3 surfaces, the web app, the API and MCP, and Kairos, the activation engine, puts every product inside the tools your team already uses.

Give Your AI Agents Context on Every Buyer

Want to try it yourself?

What the trial includes

All key features of People Research Agent, Account Research Agent and Visitor ID
The web app, browser extensions and MCP
7-day free trial, no card; or 21 days with a card

Want someone to show you?

15-minute demo

All 8 products, in one walkthrough
Shown on your own accounts

Book a demo

Want to look around first?

See how Buyer Intelligence works

4 types of Intelligence
3 surfaces: app, API and MCP
8 products, one buyer record

See how it works

Gartner Cool Vendor
G2 Top 100, 2025
Taught at Indiana Kelley
SOC 2 Type 2
GDPR compliant

Built for the security review: what your team adds, from CRM records to notes, stays inside your workspace. Visit the Trust Center

Ask AI about Humantic AIAnswers open in ChatGPT

Success!

Your request has been received.
Please check your email for a confirmation link.

Oops! Something went wrong while submitting the form.

Context Enrich: Unique Buyer Context