Datics AI
AI for MarTech

Rankly by Datics AI

Social managers see the comments worth answering first, across every platform.

Managers stop reading three platforms end to end. Rankly orders comments and messages by who is writing and what they wrote, sets junk aside, and learns from every choice the manager makes.

See it in your platform Try the demo

Built into your codebase and shipped under your name, on an engine we license to you.

murmurline.example/inbox/tidewell-coffee

Halyard and Finch · Rankly

Demo

What should I answer first for Tidewell today?

Queue ready for the manager

  • 38 items to answer first, ranked on writer and words
  • 212 set aside as junk or spam, waiting for confirmation
  • Every choice feeds the next training round

1,240 items rankedManager decidesChoices become labels

Try it step by step

Illustrative demo on a fictional agency. Not client work.

Try it step by step

Rankly on a fictional agency.

Halyard and Finch (fictional). Step through the conversation, then see what Rankly hands back, the way your Build Sprint would build it on synthetic data.

murmurline.example/inbox/tidewell-coffee

Halyard and Finch · Rankly

Demo

  • What should I answer first for Tidewell today?

Step 1 of 5

Illustrative demo on a fictional agency. Not client work.

What it hands back

murmurline.example/inbox/tidewell-coffee

Ranked inbox · Tidewell Coffee

Halyard and Finch · Facebook, Instagram and X

Rankly
Answer first
38 items · led by 2 damaged orders
Done
Writer score
Repeat customers and active followers ranked up
Done
Words score
Angry and urgent messages ranked up
Done
Set aside
212 junk or spam · manager to confirm
Waiting
Training labels
64 choices since yesterday · next round tonight
Done

The model ranks and labels. The manager answers, skips or marks spam on every item.

Illustrative demo on a fictional agency. Not client work.

What it does

What Rankly can do.

One ranked queue of comments and messages from several platforms, scored on who wrote each one and what they wrote, with junk and spam set aside, and every reply, skip or spam choice feeding the next round of training.

One queue for every platform

Comments and messages from Facebook, Instagram and X in one store and one queue.

Two scores: writer and words

One model scores the writer's activity with the page, the other scores what they wrote.

Junk and spam set aside

Items with no signal sorted out of the queue, for the manager to confirm.

Learns from the manager

Every reply, skip, ignore or spam choice becomes a label for the next training round.

How it works

Extraction brings each platform's comments, messages and writer activity into one store. Activity scores and sentiment scores feed a classifier that orders the queue, and documented APIs hand it to your web layer. The manager's choices go back into training.

Built on a comment ranking layer we have added to a running social media management platform for agencies.

Sparrow Marketing

Social inbox · Comment ranking

Social managers see the comments worth answering first, learned from their own choices

Managers dug through three platforms for the comments that mattered; now one ranked queue puts them on top and sets junk and spam aside.

Brownfield AIHuman approvalInside a live product
Read case study

SenTrac

Social listening · Campaign sentiment

Agencies see how audiences feel about a campaign, scored fairly across six channels

Agencies copied comments by hand and misread sarcasm and emoji; now SenTrac scores every comment and compares channels on one scale.

AI-native productHuman approvalIntegrations
Read case study

SenTrac

Social data · Collection within API rules

Campaign reports use only the data each platform allows, refreshed within its limits

Social APIs are gated, capped and change often; we built SenTrac's data layer so each platform's rules and limits hold and reports stay current.

Data foundationAI-native productIntegrations
Read case study

Why it sells

What Rankly does for your business.

What your agencys get, and what it does for your renewals and pricing.

Hours back for managers

The queue starts with what matters, not with what arrived last.

The brand voice stays human

The model ranks; every reply is still written by a person.

Better every week

The ranking learns from everyday choices.

Built for:Social listening and influencer platforms

Controls

What Rankly touches, and who approves.

Your agencys' data is not used to train models for anyone else and stays in your cloud. Built and tested on synthetic or test data.

  • Who uses it

    Social media managers at agencies and brands

  • What it connects to

    Your platform connections, inbox data and web layer through documented APIs

  • What a person approves

    The manager replies, skips, ignores or marks spam on every item

  • Switch per agency

    On or off for each agency, with data settings their admins control.

See all controls and how we handle social and audience data

How to get it

Two steps to a finished Rankly.

Start with a three-week Build Sprint. Add more only if you want it.

  1. First · Build Sprint · $10,000 fixed

    Managers answer the right comments first

    • One queue for every platform
    • Two scores: writer and words
    • Learns from the manager
    • In your staging, behind a feature flag
    • Delivered as pull requests
    • A test set your team reviews
    1. Week 1Setup
    2. Weeks 2 to 3Build
    3. You getRankly in your staging and a fixed production quote
    Your time
    About 2 to 3 hours a week from a product owner
    Data
    Synthetic or test data, never your agencys' customers
    The fee
    Counts toward production
    See Rankly in your platform See a sample Build Sprint Pack

  2. Then · Live in production

    A finished product, yours to run

    • Fixed quote
    • Tested before launch
    • Switch per agency
    • A finished, working Rankly in your product
    • Runs in your cloud, under your name
    • Fixed quote, agreed before we start

  3. Optional · Add more later

    Only if you want it

    More of Rankly:

    • Junk and spam set aside

    Another module:

    • Each one quoted on its own
    • Nothing ongoing unless you ask

Already built or tried AI? Get it scored with the AI Scorecard. Need something else? Start with a Planning Sprint.

FAQ

Questions about Rankly.

Does it reply to comments?

No. It ranks and labels. The manager decides to reply, skip, ignore or mark spam.

We have little labeled data. Can it still work?

Yes, as labels build up. Every manager choice becomes a label, so the ranking improves as the team works.

See Rankly on your own product.

Bring your product and one workflow. In 30 minutes we look at where Rankly fits, what it would cost to serve and what your agencys' security review will ask.

Book a 30-minute Product Review All martech modules

Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.

See Rankly in your platform