What is people and company intelligence?
People and company intelligence is the practice of researching people and organizations, interpreting current evidence against a team's criteria, and producing a decision someone can review. It sits between raw data and action: not just a record or signal, but an argued answer about who matters, why now, and what to do.
On this page, company means the organization being researched. Account is the sales term for that same company once it is part of a territory, working set, or revenue process.
Why this category exists
Contact records, company news, hiring data, social activity, and intent signals are easier to obtain than they once were. Yet the important question still falls to a person: does this information matter to our thesis, now?
More inputs do not automatically produce a better decision. A list can tell you who exists. An alert can tell you that something changed. A score can rank records. People and company intelligence does the interpretive work between those inputs and the next move.
From evidence to judgment
| Stage | Question | Output |
|---|---|---|
| Criteria | What kind of person, company, or change matters to this team? | A Persona, requirements, or research thesis |
| Evidence | What do current public sources show? | Observable facts, source links, and dates where available |
| Interpretation | Why might those facts matter to the team's criteria? | A readable reason, not only a score |
| Review | What is supported, inferred, or still unknown? | A judgment a person can accept, reject, or refine |
| Action | What would be a proportionate next move? | A research, sales, or market action grounded in the reason |
The value is the chain. A conclusion without evidence is hard to trust. Evidence without interpretation leaves the research job unfinished.
Three connected kinds of intelligence
People Intelligence
People Intelligence begins with the kinds of people and companies a team wants to find. It combines role and company criteria with relevant public evidence, then explains why each person appears.
Account Intelligence
Account Intelligence begins with a company a team already cares about. It develops a dated view of the company, what is changing, and the people who may be relevant to a possible purchase.
Audience Research
Audience Research examines the topics, posts, language, and voices that earn attention from a defined audience. It helps a team form better content and market hypotheses from observed activity.
Sales teams are Lumnis's primary commercial audience today. The category is broader than the buyer: the same evidence-and-judgment model can support research about people, companies, and markets without turning Lumnis into a generic sales automation product.
How it differs from nearby categories
| Category | Typical job | Relationship to people and company intelligence |
|---|---|---|
| Contact or sales intelligence | Supply company and contact records for prospecting | Useful input; a record does not explain why it matters to a particular team now |
| Intent data | Surface topic, web, product, or social activity that may indicate interest | Useful evidence; observable activity is not proof of a private plan |
| Account intelligence | Research named accounts, changes, stakeholders, and priorities | The closest familiar bridge to the company side of the category |
| Workflow or enrichment builder | Combine data providers and automate a configured process | Can prepare inputs or carry out a workflow; the user often designs the research logic |
| Market intelligence | Search documents, markets, competitors, or investment information | Adjacent research work, often for a different buyer and corpus |
| Revenue intelligence | Analyze calls, deals, forecasts, and execution inside the revenue process | Focuses on internal revenue activity rather than external people and company research |
These systems can complement one another. People and company intelligence is not a claim that a team should replace every database, CRM, or workflow it already uses.
Evidence, inference, and unknowns
An inspectable reading separates three things:
- Observed: a public source says or shows something, with a date where freshness matters.
- Inferred: that observation may make a person or company relevant because it matches the team's criteria.
- Still unconfirmed: public evidence cannot establish an unpublished buying plan, internal budget, or private priority.
For example, a company may publish a set of relevant job openings and a leader may discuss the same operational theme in public. Those observations can justify research or a careful conversation. They do not prove that the company is purchasing a specific product.
What a useful output looks like
A useful people or company intelligence output should let a reviewer answer:
- Which person or company is being recommended?
- Which of our requirements does it appear to meet?
- What current evidence supports that reading?
- How old is the evidence?
- What has been inferred rather than directly observed?
- What is still unknown?
- What next move is proportionate to the evidence?
Lumnis calls the combined result a reviewable opportunity: a person or account, a reason, supporting evidence, and a sensible next move.
A synthetic rep-ready intelligence brief
This example is fictional and illustrates the structure of the output. It is not a customer result or a claim that every field is available for every company.
| Brief field | Example |
|---|---|
| Company / account | A target software company already assigned to the team's working set |
| Person / role | A revenue-operations leader whose public responsibilities appear relevant to the team's thesis |
| Observed evidence | The company published a current role tied to standardizing account research, and the leader discussed the same operating problem in a dated public post |
| CRM and relationship context | When connected, the person is already in the CRM, the company/account is matched, no active deal is present, and lifecycle or native stage is available; the reviewer can add relationship knowledge separately |
| Why it may matter | The public evidence suggests the company is allocating attention to the problem; it does not establish a software evaluation or private buying plan |
| Still unconfirmed | Budget, project timing, internal decision rights, existing vendor commitments, and whether the leader owns the work |
| Suggested reviewer or owner | The existing account owner, or a sales manager if ownership is unresolved |
This is an intelligence brief, not a drafted message or an autonomous action. The reviewer checks the sources, adds any relationship knowledge the team has, and decides whether the account deserves more research, a coordinated team discussion, or no action. Lumnis does not claim to ingest prior conversation history or assign organization-wide ownership automatically.
A sales example
A sales team may define a Persona around a specific role, company profile, and operational problem. Lumnis can look for people who match those requirements, examine relevant public evidence, and show why each result may deserve attention. The rep reviews the sources and the inference before deciding whether to research further, route the account, or start a conversation.
For a named account, the team can begin with the company instead. A dated account view brings company research and relevant people into one place, making it easier to decide where deeper work is warranted.
How to evaluate a people and company intelligence product
- Can your team define its own criteria, or are you limited to a vendor's generic score?
- Can you see why a person or company was recommended?
- Are source links and as-of dates visible where available?
- Does the product distinguish an observed fact from an inference?
- Can a user correct or reject the reasoning?
- Does repeated research state its actual cadence rather than claiming “real time”?
- Are current capabilities separated from Preview or planned features?
- Can the output continue into the systems where your team works without hiding human approval?
Frequently asked questions
Is people and company intelligence the same as sales intelligence?
No. Sales intelligence usually centers on company and contact data used for prospecting. People and company intelligence can use that data, but its primary job is to interpret evidence against a team's thesis and explain why a person or company matters.
Is it the same as account intelligence?
Account intelligence is the strongest established category for the company-centered job. People and company intelligence includes that job and also covers people-centered search and audience research through the same evidence-and-judgment model.
Does it predict buyer intent?
It can identify observable activity that may be relevant to a buying thesis. It cannot confirm an unpublished private plan. A trustworthy product should show the evidence and label the interpretation as an inference.
Who uses people and company intelligence?
The lead Lumnis use case is a sales team that needs account-specific research across more people and companies than reps can investigate manually. Research, recruiting, market, and investment teams may recognize related jobs, but Lumnis is currently built and marketed first for sales.
Does the category require AI?
The defining requirement is not a chat interface or an agent label. It is the ability to turn evidence and team criteria into a useful, inspectable judgment. AI can help perform that work, but the quality of the reasoning, sources, freshness, and review controls determines whether the output is trustworthy.
See the category in practice
Explore how Lumnis applies this model to people research, named accounts, and audience research. For the operating layer between evidence and action, read Operationalizing buyer signals.
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