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See public issues before they escalate.

SONAR monitors online news, video and social media for the topics you set, filters out what is off-topic, measures public stance toward your organisation, and scores the risk of issues that start to rise. Your team reads it in one place, refreshed every 30 minutes.

SONAR Overview page in the dark theme: cards for posts, comments, users, interactions and views with change against the previous period, the Brief paragraph, the mention trend and the channel split.
Overview, demo project National Political Issues, 11 to 24 Oct 2026.
212,303
relevant mentions in 90 days, demo project
378
news feeds, YouTube channels and Telegram channels, checked daily
30 min
collection cycle for every project
14:38 WIB
last data received, 3 November 2026

Public issues rarely start on the front page. They start in comment sections, short videos and Telegram channels, and then the press picks them up. SONAR reads all of those channels in one database, with relevance rules written for your organisation, and tells your team when an issue's volume rises outside its usual pattern.

01Product

One workspace for the communications team

From the morning scan to the report for leadership. Every image below is an unedited screenshot of the demo project.

SONAR Radar: list of active issues with risk scores, the selected issue with its five score drivers, a forecast chart and a map of places mentioned.
Radar, demo project National Political Issues, 3-day window.

01 · Radar

Issues that are starting to grow, with a score and the reasons

Every two hours the latest conversation is grouped into issues and scored for risk from 0 to 100 on five drivers: volume, velocity, sentiment, spread and the share of copy-paste text. An 18-hour forecast is shown with its range.

What your team can do

  • 01Sort issues by risk, velocity or time
  • 02See when an issue is expected to peak
  • 03Put Radar on a control-room screen
SONAR Escalation page: hourly issue curve split into stages, stage summaries and the first accounts and outlets.
Escalation, demo project National Political Issues.

02 · Early warning

Every issue broken into stages

An issue is called a spike only when its hourly peak passes a statistical test against that issue's own baseline. The curve is split into trigger, amplification, peak, decay and follow-up waves, with the first accounts and outlets that carried it.

What your team can do

  • 01See who triggered it and when the press came in
  • 02Count the hours left before the issue reaches half its peak
  • 03Read per-stage narratives whose numbers have been checked
SONAR Mention explorer table: columns for media, title, sentiment, emotion, terms, views and publish time.
Mention explorer, demo project National Political Issues, 11 to 24 Oct 2026.

03 · Mention explorer

Every number opens down to the posts behind it

Mention explorer lists the articles, videos, posts and comments behind every chart. Search takes operators: quoted phrases, OR, exclusion with a minus sign, site: and author:.

What your team can do

  • 01Search with operators, for example "putusan MK" -tiktok
  • 02Filter by channel, emotion, post type and sentiment
  • 03Export results to CSV or Excel
SONAR Sentiment page: label-source bar, cards for positive, negative and net score, trend per sentiment and top words per sentiment.
Sentiment, demo project National Political Issues (tone mode), 11 to 24 Oct 2026.

04 · Sentiment

Stance toward your organisation, not just tone

A project can use tone mode or stance toward one target, such as your ministry or company. In stance mode, criticism your organisation makes of others counts as neutral. The page always states what share of labels comes from the language model and what share from the lexicon.

What your team can do

  • 01Separate stance toward your organisation from general tone
  • 02Limit charts to language-model labels only
  • 03See the most frequent words per sentiment
SONAR actor and topic network graph with a summary panel for density, sentiment and top nodes.
Network, demo project National Political Issues, 11 to 24 Oct 2026.

05 · Network

Who and what appear together in one issue

The network graph links people, organisations, terms, hashtags and accounts that appear in the same mention. The Entities page ranks the most-named names with their sentiment and channels.

What your team can do

  • 01Find clusters of related accounts and topics
  • 02See which public figures draw the most criticism
  • 03Name clusters with AI assistance
SONAR report library: saved reports with period and number of cards.
Reports, demo project National Political Issues.

06 · Reports

Reports for leadership, built from the same cards

Build a report from dashboard cards, save the layout, then export to PDF or Word. The numbers in the report match the dashboard, and the AI narrative is optional.

What your team can do

  • 01Build the weekly report once and reuse it
  • 02Export to PDF or Word
  • 03Add an AI narrative whose numbers are checked
SONAR Campaign Decoder dashboard in the dark theme: cards for videos, creators and formats, a grid of top videos by views, a performance map of views against likes, and a panel for one video.
Campaign Decoder, test campaign on the forest and land fires public issue, Oct 2026.

07 · Campaign Decoder

Which creator formats win, and the pattern behind them

Campaign Decoder breaks a TikTok and Instagram creator campaign into formats, a second-by-second script and a performance map. It also judges whether the wave of videos arose on its own or follows a patterned brief.

What your team can do

  • 01See which formats and hooks get views above the median
  • 02Compare each video with its creator's own baseline
  • 03Read the structure score and the reconstructed brief, with the evidence against it

02Decoder

Which format wins, and whether the wave is organic.

Campaign Decoder reads creator campaigns on TikTok and Instagram, whether a brand campaign or a wave of videos about a public issue. Every video is sorted into a format, its script is broken down by the second, and its performance is compared with the campaign median.

SONAR Campaign Decoder dashboard: cards for videos, creators and formats, a grid of top videos by views, a performance map of views against likes with the campaign's typical views line, and a panel for one video.
Campaign dashboard, test campaign on the forest and land fires public issue, Oct 2026. Unedited screenshot, Indonesian interface.

01

Format and script

AI groups videos into formats discovered from the campaign itself, then breaks each script into hook, brand or issue appearance, method, benefit and CTA, with timestamps.

02

Performance map

Each video is placed by views and likes against the campaign median and against its creator's usual numbers, so a video that wins on format is separated from one that wins on a large account.

03

Organic or structured

Eleven signals, from posting times to near-identical captions, are combined into a 0 to 100 score, and AI reconstructs the probable brief together with the evidence against it.

From the database

1,264
videos analysed
767
creators
59
formats found by AI
5,747
script beats extracted
5 organic · 1 mixed · 0 structured
structure score results

1,264 videos from 6 decoded test campaigns. Campaigns with sample data are not counted, and no campaign or account names are shown here. Last decoded 3 Nov 2026, 11:13 WIB.

The Organic or structured section: a 0 to 100 structure score on an organic, mixed, structured band, a chart of videos per day with the busiest 48-hour window, and the AI reconstruction of the brief.
Organic or structured: the score, posting-time pattern and reconstructed brief.
Script anatomy of one video: a coloured beat strip for hook, brand or issue appearance, method, benefit and CTA, with each beat's start second and text.
Script anatomy of one video, beats with their timestamps.

Used by

Brands and agencies
Which formats and hooks get views above the median, and which creators perform above their own baseline.
Government and organisations
Whether a wave of videos about an issue arose on its own, or follows the same patterned brief.

How to read organic or structured

  1. 01Each signal is scored 0 to 100. The higher it is, the more it looks like a brief: posts close together in time, the same hashtag bundle, near-identical captions or hooks, a uniform CTA.
  2. 02The campaign score is the weighted mean of the signals that have enough data, read as organic, mixed or structured. Campaigns with too few videos get no verdict.
  3. 03A high score means a strong pattern, not proof of payment or fake accounts.
  4. 04The reconstructed brief always lists the counter-evidence and what a person should verify, such as paid-partnership labels.
How the structure score is computed (Indonesian)

03Solutions

Used for decisions that cannot wait

Three ways organisations use SONAR. Each flow uses pages that exist in the product today.

01

Government and public agencies

Public relations, communication bureaus, control rooms

A policy is announced on Monday morning. The press office needs to know whether opposition is growing, and where.

  1. RadarA new issue appears with a risk score and a forecast of its peak.
  2. EscalationWho started it, when the press came in, and how many hours are left.
  3. MapThe regions named most often in the conversation.
  4. Response planKey messages and per-channel drafts for the team to edit.

02

Parties, organisations and NGOs

Secretariats, parliamentary groups, advocacy teams

An organisation wants to know how the public judges its position on a bill, separately from the criticism it makes of others.

  1. SentimentStance toward your organisation, not general tone.
  2. QuotesWho quotes whom in the news, with the original sentence.
  3. NetworkAccounts and figures that appear together in the same issue.
  4. ReportsA weekly report for the board meeting.

03

Brands and companies

Corporate communications, customer care

A price rise lands this week. The team wants to find complaints in video comment sections before the press quotes them.

  1. Mention explorerFilter comments by channel and emotion, search with operators.
  2. OverviewCompare comments and interactions with last week.
  3. RadarKnow when complaints cluster into one rising issue.
  4. CompareCompare two brands or two campaigns over the same period.

04Platform

One path from a public post to a response plan

Every box below runs today. Blue lines mark where numbers are checked before they are shown; circles mark where your analysts can correct the machine.

SONAR processing flowFlow diagram: public sources go to collectors every 30 minutes, then relevance rules, de-duplication, language-model classification, roll-ups and analytics, early warning, Radar and response. Analysts can correct at relevance, classification and response. The number check filters AI narratives in early warning, Radar and reports.Public sourcesnews, video, social01Collectorsevery 30 minutes02Relevance rulesproject rule score03De-duplicationcopies flagged04Classificationlanguage-model labels05Roll-ups, analyticsevery 15 minutes06Early warningspike test, stages07Radarrisk score every 2 h08Response, reportsdrafts, reportsanalysts can review and correctAI numbers checked against source data
  1. 01

    Collect

    Collectors run every 30 minutes for every project: news feeds, YouTube, Telegram, Bluesky, Google News, and data providers for TikTok, Instagram, X, Facebook and Threads.

    • Each platform's quota is logged, so volume is a consistent sample
    • Identical copies are flagged and never counted twice
  2. 02

    Filter

    Each item is scored with the project's relevance rules: anchor phrases, acronyms, names, context words and negative words. Items near the threshold are judged by a language model.

    • Rejected items are kept, with the reason
    • Analysts can restore anything rejected by mistake
  3. 03

    Understand

    A language model labels relevance, tone, stance toward the project's target, emotion, categories and a summary. Daily counts per channel and sentiment refresh every 15 minutes.

    • Manual corrections are never overwritten
    • Every page uses the same filter, so totals match
  4. 04

    Act

    Early warning and Radar flag rising issues. Response plans, key messages, per-channel drafts and reports are built from the same issue data.

    • Your team edits drafts and assigns tasks
    • SONAR never publishes to your accounts

Number check

Before an issue summary, early-warning narrative, draft, report or AI answer is shown, any sentence that cites a number not found in its source data is removed.

05Live data

Numbers from the database, not from a brochure

The charts in this section are recomputed every hour from the demo project National Political Issues. Each one states how it is computed.

Relevant mentions per day, last 90 full days

Relevant mentions per day, last 90 full daysStacked area chart: 212,303 relevant mentions in 90 days. The busiest day was 29 Oct 2026 with 6,699 mentions. YouTube and online news are the largest channels. Largest early-warning issue: 3,076 mention, 6 Oct.2k4k6k8k5 Aug19 Sept2 Nov12
  1. 1 90-day peak: 6,699 mentions, 29 Oct
  2. 2 Largest early-warning issue: 3,076 mention, 6 Oct
Demo project National Political Issues, stacked by channel, days in Jakarta time. Duplicates and off-topic items are not counted. Volume before October partly comes from archive backfill. Early-warning history is recorded from 1 October 2026. Read straight from the database, refreshed hourly.

Channel split, 30 days

  • YouTube54,998 · 61%
  • Online news28,855 · 32%
  • TikTok3,101 · 3%
  • Bluesky1,857 · 2%
  • Telegram1,278 · 1%
  • Instagram179 · 0.2%
  • Threads47 · 0.1%
  • Facebook41 · 0%
  • X35 · 0%

Relevant, non-duplicate mentions per channel, last 30 full days in Jakarta time. Comments count as mentions.

The five most-named names

  1. 1Gibran Rakabuming Raka person15,432
  2. 2Prabowo Subianto person10,911
  3. 3DPR RI organisation6,490
  4. 4Joko Widodo person4,319
  5. 5Mahkamah Konstitusi organisation4,106

People and organisations from entity recognition, counted per mention. Places, products and political parties are not shown on this public page.

Demo project sentiment

National Political Issues

tone mode

negative 31%neutral 57%positive 12%

99% of 91,776 mentions labelled

Only mentions labelled by the language model or an analyst. 99% of relevant mentions from the last 30 days are labelled so far.

Full calculation notes (Indonesian)

06Methodology

Measured accuracy, weak spots included

We tested the automatic labels against 508 mentions labelled by a person. The results are published as they are.

87.9%
relevance precision

recall 88.7%, 508 mentions

72.8%
sentiment accuracy, tone-mode project

232 relevant mentions

92.5%
spot check of live labels

40 mentions, tone-mode project

Right now 99% of the 91,776 relevant mentions from the last 30 days are labelled by the language model or an analyst. Across the whole database the figure is 100%; the rest carry lexicon labels and are marked on the Sentiment page.

See every test result
Measured accuracy, weak spots included
Sentiment, all relevant mentions67.8%Sample: 311accuracy
Tone-mode project72.8%Sample: 232National Political Issues
Stance-mode project (demo)53.2%Sample: 79about 72% when scored with codebook v2
Keyword lexicon65.3%Sample: 311fallback until model labels arrive
Relevance, precision87.9%Sample: 508recall 88.7%
Emotion, precision37.7%Sample: 508read as an indication, not a measurement
Spot check of live labels92.5% / 87.5%Sample: 40 + 40tone project / stance project

Measured on 24 October 2026 with the previous model version. A re-run with the current model has not been done yet.

What is a sample or an estimate

  • Volume is a search sample within platform quotas, not a count of every post.
  • Potential audience is estimated from follower counts and outlet audiences, not measured reach.
  • Map locations come mostly from place names mentioned in the text.
  • The copy-paste share indicates coordination; it does not prove bot accounts.
  • Radar forecasts are indicative and always shown with their range.
Read the full methodology (Indonesian)

Relevance rules you can read

Rules are written per project. This excerpt is from the demo project: "MK" only counts when capitalised, sports and foreign politics score negative, and items between the two thresholds are checked by a language model.

{
  "anchors": [
    { "p": "presiden|wapres|istana|kabinet|…", "w": 3 },
    { "p": "MK", "w": 3, "case": true },
    …
  ],
  "negatives": [
    { "p": "piala dunia|liga 1|sepak bola|…", "w": -2 },
    { "p": "bundestag|midterms|white house|…", "w": -4 }
  ],
  "threshold": { "relevant": 3, "irrelevant": 0 },
  "sentiment": { "mode": "tone" }
}
Demo project relevance rule, shortened

07Security

Your data stays where you choose

SONAR is a web application with a PostgreSQL database. Everything inside the dashed line runs in one place: your server, or a Grimmia-managed VPS in Jakarta.

SONAR deployment topologyDeployment diagram: the user's browser connects to the SONAR application. The application, PostgreSQL database, collectors and AI gateway sit inside one boundary, either your server or a Grimmia-managed VPS in Jakarta. Collectors fetch content from public sources. The AI gateway sends mention text to a language-model provider for labelling.Your server, or a Grimmia VPS in JakartaUser's browserSONAR applicationper-page access rightsPostgreSQLmentions, labels, activity logCollectorsevery 30 minutesAI gatewaymanaged by GrimmiaLanguage-model providervia the Grimmia gatewayPublic sourcesRSS, platform APIsmention text for labelling

Two deployment options

On your organisation's server or data centre, installed with the Grimmia team, or on a Grimmia-managed VPS in Jakarta. With the second option each client gets separate projects and sees only its own.

Per-page access rights

Each role gets read or read-write access per page. Access is recorded in the activity log, and API tokens can be revoked at any time.

AI numbers are checked

AI sentences that cite numbers not found in the source data are removed before they are shown. The Brief paragraph on the dashboard uses no language model at all.

What leaves the boundary

Only mention text, at most 800 characters per item, goes to the language-model provider through the gateway for labelling and summaries.

Retention

Set in the contract. When the contract ends, project data is exported for you and then deleted from Grimmia-managed servers.

Not used to train models

Grimmia does not train AI models on your data.

08Sources

Sources monitored

The source registry is checked automatically every day. Feeds or channels that fail are not used until they recover.

253

news feeds (RSS)

92

YouTube channels

33

Telegram channels

6

social platforms

Television, radio and print are not monitored yet, except what is uploaded to YouTube.

Last checked 25 Oct 2026, 13:13 WIB

See the full source list

news feeds (RSS)

National 60

Antara 10, Republika 8, Detik 6, Liputan6 5, Sindonews 5, CNN Indonesia 4, Tempo 3, Kumparan 2, Akurat, Alinea, Disway, iNews, Jawa Pos, JPNN, Jurnas, Magdalene, Medcom, Media Indonesia, Okezone News, Project Multatuli, RMOL, Tagar, The Conversation ID, Viva, VOI

Business 25

CNBC Indonesia 8, Detik Finance 4, Kontan 2, Liputan6 2, CNN Indonesia Ekonomi, IDX Channel, Investor Daily, Katadata, Kumparan Bisnis, Okezone Economy, Republika Ekonomi, Sindonews Ekbis, Warta Ekonomi

Government 18

Bawaslu RI, Pemprov Jateng, Kemenko PMK, Kementerian Pertahanan, Kementerian Perdagangan, Badan Narkotika Nasional, Lembaga Penjamin Simpanan, Pemprov Sulteng, Pemprov Aceh, Tribratanews Polda Gorontalo, Tribratanews Polda Aceh, PPID Pemprov Jateng, Pemkot Samarinda, Pemkot Malang, Pemkot Banjarmasin, Pemkab Bantul, Pemkab Karawang, Pemkab Gunungkidul

Parliament 5

Fraksi Gerindra, Fraksi PKB, Parlementaria DPR, DPRD Jawa Tengah and 1 more

Parties 5

Partai NasDem, Golkarpedia (Partai Golkar), Partai Gerindra, PKB and 1 more

International, Indonesian-language 4

Antara English, BBC Indonesia, DW Indonesia, Anadolu Indonesia

Fact-checking 1

Liputan6 Cek Fakta

Regional feeds by province 135

Jawa Timur 23, Jawa Tengah 11, Bali 7, Jawa Barat 7, Sumatera Selatan 6, Sumatera Utara 5, Bengkulu 4, DI Yogyakarta 4, Kalimantan Timur 4, Kalimantan Utara 4, Nusa Tenggara Barat 4, Papua 4, Riau 4, Sulawesi Selatan 4, Aceh 3, Banten 3, Gorontalo 3, Kalimantan Barat 3, Kalimantan Selatan 3, Kepulauan Riau 3, Lampung 3, Nusa Tenggara Timur 3, Sulawesi Utara 3, Sumatera Barat 3, Jambi 2, Kalimantan Tengah 2, Kepulauan Bangka Belitung 2, Sulawesi Tengah 2, DKI Jakarta, Maluku, Maluku Utara, Papua Barat, Papua Tengah, Sulawesi Tenggara

YouTube channels

National 29

KompasTV, CNN Indonesia, tvOneNews, Metro TV, Kompas.com, detikcom, Tribunnews, Official iNews, Seputar iNews RCTI, BeritaSatu, Narasi Newsroom, Tempodotco, TV Tempo, SINDOnews, Liputan6, TVRI Nasional, RRI NET Official, Okezone, Antara TV Indonesia, Republika Official, JawaPos TV, kumparan, IDN Times, VIVA.co.id, Media Indonesia, Tirto ID, Suara.com, Merdeka.com, Pikiran Rakyat

Regional 13

Kompas TV Jawa Timur, Kompas TV Jawa Barat, Kompas TV Jawa Tengah, Kompas TV Dewata (Bali), Kompas TV Lampung, Kompas TV Aceh, Kompas TV Makassar, Tribun Timur, TribunJatim Official, Tribun Jabar Video, TribunJakarta Official, Tribun Medan TV, Serambinews

Business 5

CNBC Indonesia, Katadata Indonesia, Kontan TV, Bisnis.com, IDX Channel

Government 30

Sekretariat Presiden, Sekretariat Kabinet RI, Kementerian Sekretariat Negara RI, Kementerian Keuangan RI, Kemkomdigi TV, Kemendagri RI, MoFA Indonesia (Kemlu), Kementerian Kesehatan RI, Kemhan RI, Kemenko Polkam RI, Kemenag RI, Kementerian Hukum RI, Info BMKG, BNPB Indonesia, KPU RI, Bawaslu RI, KPK RI, Divisi Humas Polri, Polda Metro Jaya, Mahkamah Konstitusi RI, Mahkamah Agung RI, Kejaksaan RI, TNI AD, Info BNN RI, Bank Indonesia Channel, Otoritas Jasa Keuangan, Pemprov DKI Jakarta, Humas Jabar, Pemprov Jawa Tengah, Kominfo Jatim

Parliament 4

DPR RI, TVR Parlemen, MPR RI and 1 more

Parties 9

Gerindra TV, PDI Perjuangan, DPP Partai Golkar, DPP PKB, NasDem TV, Partai Demokrat, PAN TV, Partai Solidaritas Indonesia and 1 more

International, Indonesian-language 2

BBC News Indonesia, DW Indonesia

Telegram channels 33

18 official; 15 unofficial channels (mirrors or aggregators) are flagged and filtered more strictly.

social platforms

TikTok
keywords and hashtags, third-party data provider
Instagram
keywords (Reels) and selected accounts
X
accounts and links; keywords when the paid provider is on
Facebook
pages and post links
Threads
accounts and post links
Bluesky
keywords through the public API
Google News, GDELT
news keyword search

Reached through Google News

The sites below offered no feed we could fetch directly when checked on 25 Oct 2026. Their articles arrive through Google News keyword search, and some through their official YouTube channels.

Media
Kompas.com, the Tribun network (except Tribun Kaltim), Tempo (except the main, national and business feeds), Bisnis.com, Pikiran Rakyat, Suara Merdeka, Tirto, most of Kontan, Suara.com, Merdeka, IDN Times, tvOne, Beritasatu, Kompas.id, KompasTV
Government
Polri, Kemendagri, KPK, MK, MA, Komdigi, Setkab
Parties
PDI Perjuangan, Demokrat, PSI

09FAQ

Frequently asked questions

Does SONAR monitor everything on social media?

No. SONAR collects search results for the keywords, accounts and links you set, within each platform's quota. The result is a consistent day-to-day sample of the conversation, enough to read trends and issues, but not a count of every post.

How accurate are the sentiment labels?

On a 508-mention test set, language-model labels were right 67.8% of the time for relevant mentions and 72.8% in the tone-mode project. Stance mode is still at 53.2% against the old test set. Details are in the accuracy section above and on the methodology page.

Can we correct wrong labels?

Yes. Analysts can change sentiment or mark a mention off-topic in Mention explorer. Manual corrections always win and are never overwritten.

How quickly does new data arrive?

Collectors run every 30 minutes, language-model labels are added every 10 minutes, and Radar is recomputed every two hours. The statistics on this public page refresh hourly.

Can we add our own sources?

Yes. Keywords, accounts, Telegram channels and post links are set per project. New RSS feeds and YouTube channels are added to the registry and checked automatically before use.

Where is our data stored?

On your organisation's server, or on a Grimmia-managed VPS in a Jakarta data centre. Mention text is sent to a language-model provider for labelling; Grimmia does not use it to train models.

Are private citizens' accounts monitored?

SONAR only collects publicly accessible content. Private accounts and closed groups are not collected. Individual posts are visible only to that project's users, never on public pages like this one.

Can SONAR prove that a wave of videos was paid for?

No. Campaign Decoder gives a 0 to 100 structure score from eleven signals, such as posts close together in time, the same hashtag bundle and near-identical captions. A high score means a strong pattern, not proof of payment. Every result lists the counter-evidence and what a person should check, such as paid-partnership labels and account history.

Can we use SONAR data in our own systems?

Yes. Admins can create API tokens to read analytics data, and mentions can be exported to CSV or Excel. Tokens can be revoked at any time.

10Contact

See SONAR working on your topic

Tell us what you want to monitor. We prepare a demo with data on that topic, then put together a quote.

A quote depends on

  • the number of projects and users
  • the channels enabled, since some use APIs paid per request
  • data volume and how long it is kept
  • deployment on your server or managed by Grimmia

Farid Mahardika, Grimmia Intelligence