Who we are
The Balanced News is a news-analysis platform published by Ambasync Solution Pvt Ltd, an Indian company founded in 2024. We analyse how India's 50+ major news outlets cover the same stories — surfacing political bias, sentiment, and coverage gaps so readers can see the complete picture instead of a single outlet's framing.
Our mission
Indian news coverage is fragmented across ideological lines — left-leaning, right-leaning, centrist, regional-language, English-language outlets each tell a different version of the same story. For most readers this means living inside a single outlet's perspective without realising it. We built The Balanced News to change that: one place where you can see how every major source is framing a story, backed by transparent bias scoring and sentiment analysis.
Independence and ownership
The Balanced News is wholly owned by Ambasync Solution Pvt Ltd. We do not take editorial direction from advertisers, sponsors, political parties, or media partners. Advertising served on our pages is programmatic and has no bearing on bias scoring, Lens Score calculation, or source inclusion. See Editorial Standards for the full policy.
The editorial team
Every article analysis on The Balanced News carries a named human author — the editor responsible for that beat — and a named reviewer who checks the analysis before publication.

Ojas Kale
Founder & Editor
Ojas Kale is the founder of The Balanced News and CEO of Ambasync Solution Pvt Ltd. He built India's only news platform with AI-powered bias detection to combat media polarization and help readers see the complete picture across 50+ news sources. As editor-in-chief, Ojas sets the editorial standards every published story is held to: multi-source coverage analysis, transparent bias scoring, honest disclosure that the underlying analysis is machine-generated and reviewed by a named human before going live, and a corrections policy with a public log. He reviews escalations across all beats — politics, business, technology, culture, accountability — and personally signs off on the methodology behind every measurement TBN publishes, including the political-inclination spectrum (Left/Centre/Right percentages), sentiment scoring, and the Lens Score that quantifies the gap between a story's public importance and the actual media coverage it receives. Ojas's work focuses on making media-bias detection legible to readers who don't have time to compare ten outlets manually, and on building the Indian news ecosystem's first openly-documented bias dataset that researchers and journalists can cite. He oversees TBN's editorial standards, corrections policy, and partnerships, and is the point of contact for press, research, and accountability queries.

Ashwin Alsi
Technology Editor
Ashwin Alsi covers the intersection of technology and media at The Balanced News. He writes about AI, deepfakes, algorithmic bias, and how technology is reshaping how India consumes news. Within TBN's editorial workflow, Ashwin reviews the AI-generated bias analysis for stories in the technology, science, and digital-policy beats before they go live — checking that framing, sentiment, and source attribution are correctly identified, that technical terminology is used accurately, and that emerging concerns (synthetic media, model-generated misinformation, recommender-system effects) are surfaced where relevant. He tracks how Indian and international outlets cover AI governance, data-protection law, semiconductor and platform regulation, and the practical impact of new technology on journalism itself. Ashwin contributes long-form pieces on deepfake-detection techniques, how recommendation algorithms reshape what readers see, and how legitimate AI-assisted journalism differs from low-quality scaled content. He is particularly attentive to stories where technical claims need verification — viral video provenance, alleged exploits, statements attributed to AI systems — and flags them for additional source review when TBN's automated analysis cannot independently confirm them. Ashwin also maintains TBN's internal documentation on the Bias Engine's measurement methodology and writes the reader-facing explainers on how political bias and sentiment are scored.

Prajakta Kale
Political Analyst
Prajakta Kale is a political analyst at The Balanced News who tracks how Indian media frames political events. She specializes in election coverage, party manifestos, and legislative analysis across the political spectrum. Prajakta is the named reviewer for TBN's coverage of politics, national affairs, and international stories — she checks the AI-generated bias breakdown against the actual coverage on each beat, validates that left/centre/right framing is being attributed to the right outlets, and flags edge cases where a story's framing is more nuanced than a single bias percentage can capture. Her work focuses on how language choices, headline framing, source selection, and which voices are quoted differ when the same political event is reported by national English dailies, regional-language outlets, and digital-first publications. Prajakta tracks election cycles at state and central level, parliamentary debates, party-position evolution between manifestos and statements, judicial-political intersections, and the meta-coverage question of which political stories get sustained attention versus which fade after the first news cycle. She is especially attentive to coverage gaps — events that one set of outlets cover prominently while another set ignores — because those gaps are where the Lens Score reveals the most about Indian media's editorial priorities. Prajakta also writes long-form analysis for /insights on durable framing patterns and recurring vocabulary across the Indian political-media landscape.

Mrunal Wange
Business & Economy Editor
Mrunal Wange writes about business, finance, and economic policy at The Balanced News. She breaks down how markets, trade deals, and fiscal policy are reported differently across Indian media outlets. Within TBN's editorial workflow, Mrunal is the named reviewer for the business, crypto, and economic-policy beats — she validates the AI bias analysis against actual coverage, checks that market terminology and numeric claims are correctly identified, and ensures that the sentiment scoring distinguishes between an outlet's editorial position and the underlying economic facts. She tracks how the same earnings release, RBI policy decision, budget announcement, or trade pact is reported by national pink-press outlets, English-language broadsheets, regional business dailies, and digital-first finance publications, surfacing differences in which numbers get highlighted, which analysts get quoted, and which sectoral implications get foregrounded. Mrunal pays particular attention to coverage patterns around mergers, IPOs, corporate-governance disputes, regulatory enforcement actions, and sectoral cycles (banking, IT services, real estate, energy, FMCG), where outlet ownership and investor relationships can produce systematically different framings. She also writes reader-facing explainers on how to read corporate disclosures and how to spot common business-journalism patterns — sourced primarily from a single press release, lifted from an analyst note, or the rare independent reporting — and contributes the business-side methodology notes that feed into TBN's published bias data.

Jitesh Dammani
Media Literacy Writer
Jitesh Dammani is a media literacy advocate at The Balanced News. He writes practical guides on spotting fake news, understanding media ownership, and navigating filter bubbles in Indian media. Jitesh focuses on the reader-side of TBN's mission: turning the technical machinery of bias detection, sentiment scoring, and Lens Score into clear, useful guidance that any reader can apply to their everyday news consumption. He covers the most common vectors of misleading or low-quality information in the Indian context — forwarded WhatsApp claims, regional-language viral videos, decontextualised clips, and the AI-generated synthetic content that increasingly circulates ahead of elections and during high-emotion news cycles — and writes verification walkthroughs that prioritise checks readers can actually do themselves. Within TBN's editorial workflow, Jitesh is the named reviewer for health and media-meta coverage, beats where reader harm from misinformation is most direct. He examines the AI analysis for clarity (is the framing actually understandable?) and accuracy (does the bias breakdown match what a reader would see if they read the underlying sources?). He also maintains TBN's library of media literacy explainers, including ownership maps of major Indian outlets, the legal and political relationships that influence editorial positions, and the recurring narrative patterns — false-balance, manufactured outrage, both-sides-ism on settled facts — that recur across the Indian news ecosystem. Jitesh's long-form pieces aim to make TBN's analytical output usable: readers should leave each story knowing not just which way coverage leaned but why, and what they would have noticed if they had read the originals.

Dushyant Deshmukh
Investigative Writer
Dushyant Deshmukh covers underreported stories and investigative analysis at The Balanced News. He focuses on accountability journalism, coverage gaps, and stories the mainstream media overlooks. Within TBN's editorial workflow, Dushyant is the named reviewer for the crime and accountability beats, and he reviews any story where TBN's Bias Engine has flagged one or more accountability indicators — financial irregularity, abuse of power, systemic failure, attempted cover-up, rights violations, electoral malpractice, environmental violation, public-safety hazard, or sexual misconduct. His role is to validate that the AI's classification matches the substance of the underlying coverage and to flag stories where the Lens Score is high (signalling a significant gap between public importance and the actual volume of coverage) but mainstream attention has lagged. Dushyant tracks the patterns by which accountability stories enter and leave Indian news cycles: which outlets follow up after the initial story, which let the story fade, which actively reframe it. He writes long-form analysis on investigative-coverage gaps in areas like public-procurement irregularities, judicial-process delays, environmental clearances, and regulatory enforcement, and contributes the methodology notes that explain how TBN's accountability-indicator detection works and how readers can use the Lens Score to find stories that mainstream media has not given the attention their public importance would justify. He also corresponds with researchers and journalists who use TBN's coverage-gap data for their own reporting.

Aniket Awate
Culture & Digital Media Writer
Aniket Awate writes about digital media culture, YouTube politics, and entertainment news coverage at The Balanced News. He tracks how social media and influencers shape public opinion in India. Aniket is the named reviewer for TBN's entertainment, lifestyle, and social-media beats — categories where bias analysis often has to account for digital-native outlets, creator economies, and the increasingly blurred line between entertainment and political commentary. He examines TBN's AI bias output for these stories to ensure that the framing accurately reflects how the same news event is reported by traditional film-and-television journalism, by digital-first culture publications, by YouTube and podcast commentators, and by social-media accounts with audience reach comparable to mainstream outlets. Aniket's coverage focuses on the ecosystem effects of the platform economy on Indian media: how influencer endorsements function as political signalling, how YouTube channels with overt political alignment shape mainstream news framing, how entertainment-news coverage of celebrity political statements becomes its own political story, and how regional-language digital content creators are reshaping local news consumption. He writes long-form analysis on the recurring patterns in Indian pop-culture commentary, the relationships between film studios and entertainment-news outlets, and how the language of fandom and outrage migrates between entertainment and political discourse. Aniket also contributes the methodology notes that govern how TBN's Bias Engine handles outlets where reach, ownership, and editorial structure look very different from those of traditional newsrooms.
Full bios and published work: our writers and analysts.
Transparency and accountability
- Our Editorial Standards page explains exactly how our analysis is produced, including AI disclosure and human-review process.
- Our Corrections Policy explains how to report errors and how we respond.
- The bias-detection methodology is documented at How Bias Detection Works.
- The Lens Score methodology is documented at What is Lens Score.
Platform Features
A comprehensive suite of 24 tools designed to help you navigate today's complex media landscape and make informed decisions.
Media Comparison
Compare how different media outlets cover the same story
Cross-Source Comparison
View how different media outlets cover the same news story side by side
Source Count Indicator
See how many outlets are covering a specific story at a glance
Media House Labeling
Clearly identify each source with their logo and name
Perspective Switching
Easily toggle between different outlets' coverage of the same event
Timestamp Display
Track when each article was published to see how coverage evolves
Source Reliability
Understand the credibility of different news sources
Bias Analysis
AI-powered political bias detection and sentiment analysis
Political Bias Meter
Visual scale showing left-center-right political leaning of articles
Bias Percentage
Numerical representation of political bias intensity
Sentiment Score
Measures emotional tone from negative to positive on a scale
Sentiment Visualization
Color-coded bars for quick sentiment assessment
Source Bias History
Track patterns of bias across multiple stories from the same outlet
Topic Analysis
See how bias varies across different news topics
Multilingual Support
Read news in six Indian languages with regional context
Six Indian Languages
Full support for Hindi, Marathi, Gujarati, Tamil, Telugu, and Bengali
Language Switching
Seamlessly transition between languages with a single tap
Regional News Sources
Access native language publications from across India
Translation Quality
Natural language processing for accurate translations
Language-Specific Bias
Algorithms calibrated for each supported language
Cultural Context
Understand regional perspectives on national and global news
Other Features
Summaries, custom feeds, and more for a better reading experience
Four-Bullet Summaries
Get essential points from each article in a concise format
Custom Feed Creation
Create up to six personalized news feeds based on your interests
Good News Section
A dedicated section for positive stories and uplifting content
Dark Mode
Eye-friendly design for comfortable reading in any environment
Offline Reading
Access saved articles without an internet connection
Cross-Device Sync
Enjoy a consistent experience across all your devices
Frequently Asked Questions
What is The Balanced News?
The Balanced News is India's leading unbiased news platform that uses AI to detect and display political bias in news coverage. We aggregate 50+ Indian news sources and show you how left, center, and right media outlets cover the same stories differently.
How does The Balanced News detect bias?
Our AI analyzes multiple factors including political entity coverage, framing, language tone, word choice, and issue positioning. Each article receives a bias score showing its position on the political spectrum as Left %, Center %, and Right % - always summing to 100%.
Is The Balanced News affiliated with any political party?
No, The Balanced News is completely independent and not affiliated with any political party, media house, or organization. We don't editorialize or take political positions. Our goal is to show all perspectives transparently so users can form their own opinions.
How is The Balanced News different from other news apps?
Unlike traditional news apps that show one perspective, The Balanced News aggregates 50+ sources and shows you exactly how different outlets cover the same story. We group articles by topic and use AI to analyze bias, helping you see the complete picture instead of being stuck in a filter bubble.
Who founded The Balanced News?
The Balanced News was founded in 2024 by Ojas Kale with a mission to combat media polarization in India by making news bias transparent and helping users become more informed news consumers.
Our Team
The Balanced News was founded in 2024 by Ojas Kale with a team of writers and analysts covering politics, technology, business, media literacy, and investigative journalism.
Meet Our Writers & Analysts