Agify

#284 most-used

Predict age from first names for smarter contact enrichment

CRMMarketingAnalyticsHRDeveloperLead Generation

Agify.io is an age prediction API that infers the statistical age of a person from their first name using a database of millions of samples. Connect it to Actionist and your agents can enrich CRM contacts with age brackets the moment they are created, segment campaign audiences by demographic cohort in a single batch, run country-localised predictions for international contact lists, monitor API usage against monthly quotas, and produce aggregate age-distribution analytics for diversity reporting — all without storing personal birthdate data.

Average time saved
6 hours
per person · per month
≈ 1 workdays back

Eliminates manual work. Agents eliminate manual demographic research for sales reps, manual audience segmentation for marketing, and manual enrichment runs for operations — all replaced by scheduled batch predictions that run unattended.

Schedule

What your Agify agent runs on autopilot

A week of scheduled jobs your Actionist agent will execute on your behalf.

28Scheduled jobs
7Agents at work
24/7Always on
Agents
Wed–Fri
Wed
Thu
Fri
7a
8a
9a
10a
11a
12p
1p
2p
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6p
Multi-app workflows

Agify × every other app you use

End-to-end automations that span multiple apps — each one a real business outcome.

6Workflows
6Apps spanned
~21 hrsSaved / week
6Personas served
For sales
Featured4 apps

New HubSpot contact enriched with age bracket on creation

When a new contact is created in HubSpot, the agent predicts their age from the first name, translates it to an age bracket, writes the bracket to a custom HubSpot property, and logs the enrichment to a Google Sheets tracker. The sales team sees a Slack message with the contact's predicted generation before the lead is even assigned to a rep.

~10 hrs

Time saved for your team — every week, on autopilot

The flow
Trigger·When a new contact is created in HubSpot
Result
Write age bracket to custom contact propertyPost new lead summary with age bracket to #sales channelLog contact name, predicted age, and confidence count to enrichment tracker
The win
Saved per run
15 min
Runs / week
~40×
Every new lead has demographic context before the first rep call
Driven bySales Agent
ROI

Savings

What your team gets back — two angles: what you stop doing manually, and what that's worth.

Without Actionist

What you do manually today

With Actionist

What your agent runs for you

  • Sales
    30 min / week
    Manual lead demographic research

    Reps manually look up demographic signals for new leads — checking LinkedIn profiles, guessing from email tone, or simply skipping demographic context altogether.

    Sales Agent
    0 min
    Agent enriches every lead with an age bracket on creation

    When a new lead is created in HubSpot, the agent calls Agify, translates the predicted age into a bracket, and writes it to the contact property before any rep sees the record.

  • Marketing
    45 min / week
    Manual demographic segmentation

    The marketing team manually reviews audience lists, applies demographic assumptions based on industry or channel, or forgoes age segmentation entirely because it takes too long to do at scale.

    Marketing Agent
    0 min
    Agent segments the full campaign audience by age cohort in one batch

    The marketing agent submits the entire audience list to Agify in one call, receives age brackets for every contact, and writes the cohort tags to the email platform before the creative team starts drafting.

  • Customer Support
    12 min / week
    No demographic context on tickets

    Support agents have no demographic context beyond what the customer volunteers. Communication style adjustments — formal vs casual, technical vs simplified — are guesswork.

    Customer Support Agent
    0 min
    Agent appends age context to every incoming support ticket

    For each new support ticket, the agent predicts age from the customer's first name and prepends a one-line demographic note to the agent's sidebar — the support team adapts their communication style from the first response.

  • Human Resources
    20 min / week
    No age diversity analytics without self-reported data

    HR can only report on age diversity when candidates self-report age or birthdate, which many applicants decline. Demographic analytics are incomplete or absent from most hiring reports.

    Human Resources Agent
    0 min
    Agent computes applicant-pool age distribution from first names weekly

    The HR agent batches all applicant first names through Agify each week, computes the age-bracket distribution, and appends aggregate stats to the diversity metrics report — without storing individual predictions.

  • Finance
    15 min / week
    Reactive API limit management

    Finance only discovers the Agify quota has been exceeded when an enrichment batch fails. The team scrambles to upgrade the plan or defer jobs, leaving the CRM partially enriched until the billing cycle resets.

    Finance Agent
    0 min
    Agent monitors API quota daily and alerts before limits are hit

    The finance agent reads Agify's rate limit headers daily, logs remaining quota, and posts an alert if the account is on track to run short — enrichment batches are deferred rather than failing mid-job.

  • Operations
    60 min / week
    Ad hoc manual enrichment runs

    Enrichment is done manually when someone remembers to run it, using exported CSVs, a browser-based API tool, and copy-paste back into the CRM — a process that takes hours and leaves gaps in the data.

    Operations Agent
    0 min
    Agent runs the full CRM enrichment sweep every Monday unattended

    The operations agent reads all unenriched contacts, validates name quality, batches clean names through Agify, and writes brackets back to the CRM — the database team starts every week with fully enriched contact data.

  • Legal
    10 min / week
    Manual compliance checks on demographic data processing

    Legal must manually review the enrichment pipeline configuration, check that individual age scores are not being stored, and interview the data team on use cases — a process that happens quarterly at best.

    Legal Agent
    0 min
    Agent audits the enrichment pipeline weekly for governance compliance

    The legal agent reviews the enrichment configuration each week, verifies age predictions are only used in aggregate analytics, and logs a compliance check result to the audit trail — without any manual document review.

+ 100s of other Agify automations
Average time saved
19 hrs / person / month
Calculator

Calculate what your team saves

Team size
8 people
Hourly rate
$20 / hr
Hours saved / week
12
Hours saved / year
600
Annual ROI
$12,000

Based on Agify's typical team usage — the visible tasks plus a few other automations the agent runs: ~1.5 hrs / person / week of admin work automated.

Connect

How to plug Agify into Actionist

Pick the connection method that suits your environment.

Agify authenticates via a simple API key passed as a query parameter. Generate your key in the Agify dashboard and paste it into Actionist. The free tier covers 2,500 name lookups per month.

1
Sign up at Agify.io

Go to agify.io and sign up for a free account. Free accounts include 2,500 requests per month.

2
Copy your API key

After signing in, open your Agify dashboard and copy the API key shown there. Treat it like a password.

3
Paste into Actionist and test

In Actionist, find Agify in the Apps tab, click Connect, paste your API key, and click Test connection. The agent runs a test name prediction to confirm the key is valid.

Credentials you'll need
API Key*
Sign up at agify.io → copy your API key from the dashboard
Actions

12 actions your agent can call

Read and write operations available to your Actionist agent.

FAQs

Questions about Agify + Actionist

How does Actionist connect to Agify?
Go to the Apps tab, find Agify, and click Connect. Agify uses API key authentication. Sign up at agify.io, copy your API key from the dashboard, then paste it into the API Key field in Actionist. The agent runs a test call with a sample name to confirm the key works before any automation runs.
How many name lookups can I run per month?
Agify's free plan includes 2,500 name lookups per month. For higher volumes, paid plans are available at agify.io with increased monthly quotas. Actionist exposes the rateLimit.remaining value in every response, so your agent can monitor usage and alert you before the limit is reached. For bulk enrichment tasks, schedule them to spread requests evenly across the month.
Can Agify predict age differently by country?
Yes. Agify supports an optional country_id parameter (ISO 3166-1 alpha-2 code, e.g. US, GB, DE) that localises the age prediction for names that skew differently by country. For example, 'Emma' predicts differently in Germany than in the United States because the name's historical popularity peaks vary by region. Pass the country code when your contact list has a known country, and omit it for global datasets.
How confident is Agify's age prediction?
Agify returns a count value alongside the predicted age. This count represents the number of people in Agify's statistical sample who share that name. A higher count means the prediction is backed by more data and is therefore more reliable. Names with a count below a few hundred should be treated as indicative estimates rather than confident predictions.
What are the most common ways teams use Agify with Actionist?
The most common use cases are lead scoring and segmentation (enriching contact records with an estimated age bracket for targeting), CRM personalisation (appending demographic context to outreach), HR screening pipelines (age-bracket filtering for workforce analytics), and e-commerce personalisation (routing visitors to age-appropriate product ranges based on name-derived estimates).
Does Agify return an age range or a single number?
Agify returns a predicted age as an integer, not a range. However, the prediction is statistical, not individual-level. Actionist agents typically translate the raw age into an age bracket (e.g. 18-24, 25-34, 35-44) before writing it to a CRM or analytics system. You can configure the bracket thresholds in your agent's instructions, and the agent will apply them automatically before updating each record.
Is using Agify for demographic enrichment privacy-compliant?
Agify predicts age from the statistical distribution of people with that first name — it does not process personal identity data, and no individually-identifiable information is required or stored by the API. The API only receives the name string and an optional country code. Consult your organisation's data governance team before using demographic enrichment outputs in decisions that affect individuals.
Can Agify look up multiple names at once to avoid hitting rate limits?
Agify supports batch requests natively — you can submit an array of names in a single API call and receive an array of age predictions in return. Actionist agents use this to process a list of contacts from a Google Sheets column or a CRM export in one efficient call rather than making hundreds of individual requests. This is the recommended approach for bulk enrichment jobs.
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