Three steps from raw data to clear outcome predictions.
01
We collect booth-level data
Official ECI voter rolls, 2001–2021 results, and real-time alliance signals — all from primary sources.
02
We simulate thousands of elections
Each run models vote share by constituency, factoring regional swings, alliance transfers, and incumbency.
03
We estimate likely outcomes
Seat projections with confidence intervals — a range reflecting genuine uncertainty, not false precision.
Advanced methodology
Bayesian modelMonte Carlo (10,000 runs)6-zone regional swingAlliance transfer efficiencyECI 2026 electoral rolls
Why trust VakkuCheck?
Built on primary sources
🗳️
Official election data
ECI voter rolls and published results. No third-party aggregators.
🔍
Transparent methodology
Every assumption documented. Confidence intervals shown, not false precision.
⏱️
Continuously updated
Live signal ingestion — alliance changes and field signals update projections.
📌
Source links on every insight
Each forecast card cites its data source with timestamps.
Our Inspiration
"Inspired by the Kudavolai — one of the world's earliest voting systems, used by Chola kings at Uttiramerur, Tamil Nadu, around 920 CE."
A NilamLabs LLC product
The Platform
We can build this platform for your state. Your constituency.
VakkuCheck is not just a Tamil Nadu product. The engine underneath — Bayesian vote-share modelling, constituency-level data ingestion, alliance fluidity simulation, and AI narrative generation — is fully state-agnostic. Give us your electoral rolls and historical results. We give you a live, signal-driven forecast platform.
Interested?
Let us build your election intelligence platform
01 · Model
Model input weights
🗳️
Historical Results
Vote share per constituency across up to 5 election cycles. Establishes the Bayesian prior for each seat.
Weight: 35%
👥
Voter Demographics
Official electoral rolls — caste, religion, gender, age cohort ratios per booth. Informs alliance transfer efficiency.
Weight: 25%
🤝
Alliance Configuration
Real-time party-to-alliance mapping. Each seat-sharing update propagates immediately through the simulation layer.
Weight: 20%
📍
Regional Swing
Zone-level swing factors (e.g., Kongu belt, Delta region). Captures sub-state political geography unavailable in statewide models.
Weight: 12%
📡
Live Signals
AI-ingested news, rally reports, defection signals, and field intelligence. Adds recency weighting to the prior.
Weight: 8%
02 · Engine
How the Forecasting Engine works
1
Bayesian Prior Construction
For each of the 234 constituencies, we construct a Bayesian prior from historical vote shares (2001–2021), weighted by recency. Priors encode party strength, incumbency advantage, and community-level loyalty patterns.
2
Alliance Transfer Simulation
When alliances change, vote-transfer coefficients are applied per community type (e.g., Vanniyar vote in PMK-NDA alliance). Transfer efficiency is modelled as a probability distribution, not a fixed percentage — capturing real-world voter defection rates.
3
Monte Carlo Simulation (10,000 runs)
We simulate the election 10,000 times. Each run draws from vote-share distributions with national swing, regional shock, and constituency-specific noise. Output: probability distributions for seat counts, not point estimates.
4
AI Signal Ingestion
The AI agent runs continuously, parsing news, social media, party statements, and field reports. Each signal is classified by type (alliance shift, candidate change, rally attendance), reliability, and recency — then updates the model prior.
5
Narrative Generation
The AI analyst layer translates probability outputs into plain-language insights: "Why is constituency X leaning NDA despite 2021 DMK win?" The answer is derived from the model's feature weights, not hallucinated.
03 · Scale
Why our architecture scales across South Asia
🔌 Data-source agnostic
Ingests ECI XML, PDF gazettes, CSV rolls, and scraped results. Any election commission format. Any script (Tamil, Telugu, Malayalam, Bangla, Devanagari).
🏗️ Constituency-model architecture
Each constituency is an independent model unit. Scaling from 30 seats (Puducherry) to 543 seats (Lok Sabha) is a configuration change, not a rebuild.
🌐 Alliance fluidity engine
Handles coalition complexity at Indian-election scale: multi-party alliances, seat-sharing disputes, last-minute defections. The same engine works from Tamil Nadu to West Bengal.
📡 AI signals in any language
The signal ingestion layer uses multilingual LLMs. Tamil, Telugu, Sinhala, Bangla, Urdu — political signals are parsed and classified regardless of source language.
Coverage roadmap: Tamil Nadu 2026 → Puducherry 2026 → Bihar 2025 → West Bengal 2026 → Sri Lanka → Bangladesh → Pakistan provincial elections. The architecture is the same. The data changes. The insights remain local.
04 · Principles
Our principles
📊
Data over narrative.Every forecast is traceable to its inputs. We publish our assumptions. We show confidence intervals, not just point estimates. Uncertainty is information.
🔓
No opinion polling bias.We do not conduct surveys. Our model is built entirely on primary sources: official ECI data, published results, and publicly available electoral rolls.
⚖️
Alliance-neutral.We model all alliances with the same rigour. The model does not favour any party. Our signal agent is instructed to flag, not amplify — to report what the data says, not what any camp wants heard.
🔬
Falsifiable forecasts.We publish our predictions before results. We will publish our accuracy analysis after May 4, 2026. Accountability is built in from the start.
🌱
Civic infrastructure, not media product.VakkuCheck is built to serve voters, researchers, and civic organisations — not to drive clicks or generate controversy. The Kudavolai was a civic institution. So is this.
Ready to build your state's election intelligence platform?
We work with political research teams, media organisations, civic groups, and state-level parties across South Asia.
About VakkuCheck
Election intelligence built for everyone.
VakkuCheck is a civic intelligence platform built by NilamLabs LLC. We believe election data should be transparent, accessible, and useful — not locked behind jargon or paywalls.
🏺
The Kudavolai Inspiration
Named after one of the world's earliest secret ballots — used in Tamil Nadu around 920 CE under the Chola dynasty at Uttiramerur, where ballot leaves (olai) were placed in a pot (kuda) and counted openly. Democracy has deep roots here.
🏢
NilamLabs LLC
"Nilam" (நிலம்) means land or soil in Tamil — grounded, rooted, real. We build civic intelligence tools that connect people to data that matters. Tamil Nadu 2026 is our first major deployment.
Where we are going
Tamil Nadu 2026 is our proof of concept.
The architecture — Bayesian priors, constituency-level data, alliance fluidity engine, AI narrative layer — is state-agnostic. We are building toward a full Indian and South Asian election intelligence network.
🇮🇳
India — State Rollout
✅ Live Now
Tamil Nadu 2026
234 seats · April 23
✅ Live Now
Puducherry 2026
30 seats · April 9
🔜 Next
Bihar 2025
243 seats
🔜 Next
West Bengal 2026
294 seats
Roadmap
Lok Sabha 2029
543 seats
Roadmap
Kerala · AP · Telangana
South India coverage
🌏
South & South-East Asia
🇱🇰
Sri Lanka
Provincial & Parliament
🇧🇩
Bangladesh
National Parliament
🇵🇰
Pakistan
Provincial elections
🇲🇾
Malaysia
State elections
Our Principles
What we stand for
📊
Data over narrative. Every forecast is traceable to its inputs. We publish our assumptions and show confidence intervals, not just point estimates.
🔓
No opinion polling bias. Built entirely on primary sources: official ECI data, published results, electoral rolls. No surveys. No paid respondents.
⚖️
Alliance-neutral. We model all alliances with the same rigour. The model does not favour any party. Signals are reported, not amplified.
🔬
Falsifiable forecasts. We publish predictions before results. Accuracy analysis will be published after May 4, 2026. Accountability is built in.
🌱
Civic infrastructure, not media product. Built to serve voters, researchers, and civic organisations — not to drive clicks or generate controversy.
"Democracy is too important to leave to opacity."
Get Started
Try the Platform
Explore Tamil Nadu 2026 with demo credentials, or book a live walkthrough — we'll show you how the platform works and how we can build it for your state.
🆓 Free Access
Create your account — start immediately
✅ 234 constituency win probabilities
✅ Live AI signal feed
✅ Alliance tracker + voter data
✅ Pondicherry 2026 platform
📅 Live Demo
Book a 30-min walkthrough
We'll walk you through the platform live, answer your questions, and discuss how to deploy it for your state or research project.
✅ Live product walkthrough
✅ Q&A with the team
✅ Custom deployment discussion
✅ Methodology deep-dive (optional)
Contact Us
Get in touch
Whether you're a researcher, journalist, political team, or civic organisation — we'd love to hear from you.
✅
Message sent!
We'll get back to you within 24 hours.
Or email us directly: admin@nilamlabs.ai
Historical Data
TN Elections — 2001 to 2021
Six election cycles. The pendulum swings every 5 years.
2021
DMK — 159 seats vs AIADMK 66
MK Stalin wins historic majority. DMK ends 10-year AIADMK rule.
TURNOUT
74.3%
2016
AIADMK — 135 seats vs DMK 89
Jayalalithaa wins second straight majority. Historical rarity.
TURNOUT
74.6%
2011
AIADMK — 203 seats vs DMK 23
Landslide anti-incumbency against DMK. AIADMK sweeps.
TURNOUT
77.3%
2006
DMK — 96 seats vs AIADMK 61
DMK alliance returns to power. Congress key partner.
TURNOUT
64.1%
2001
AIADMK — 132 seats vs DMK 31
Jayalalithaa returns from exile to sweep polls.
TURNOUT
68.2%
Access full constituency-level historical data inside the platform
Legal
Terms of Service
Last updated: April 2026 · NilamLabs LLC
1. Use of Service
VakkuCheck is provided by NilamLabs LLC for informational and research purposes. Election forecasts are probabilistic model outputs — not guarantees of electoral outcomes.
2. Acceptable Use
You may use VakkuCheck for personal research, journalism, academic work, and civic engagement. You may not scrape, resell, or republish our forecasts without written permission.
3. Data Sources
We use publicly available data from the Election Commission of India (ECI), official electoral rolls, and published election results.
4. Disclaimer
Forecasts are statistical estimates with inherent uncertainty. NilamLabs LLC is not responsible for decisions made based on forecast outputs.
5. Contact
Questions: admin@nilamlabs.ai
Legal
Privacy Policy
Last updated: April 2026 · NilamLabs LLC
What we collect
We collect your email address when you create an account. We do not collect personal voter data, political affiliation, or location beyond what you voluntarily provide.
How we use it
Your email is used solely for authentication. We do not sell, share, or rent your personal data to any third party. No advertising.
Cookies & local storage
We use browser localStorage to remember your session and platform preferences. No third-party tracking cookies.
Election data
All election data is sourced from public ECI records. We do not associate voter personal identity with constituency data.
Contact
Privacy: admin@nilamlabs.ai
Win probability
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Win probability for all 234 Tamil Nadu constituencies
