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I was always confident that Mind Webs would evolve into a full-fledged company capable of creating real impact for businesses and people across the country.
Subhra Bishnu
Co-Founder & Director - OrangeTree AI
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DataSense answers spatial intelligence questions across climate, infrastructure, ESG, regulation and research.
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Emission heatmap · Delhi NCR (CO₂)
Speed km/h35
Direction °200°
24h sim00:00
15m / sec
NOx weekly trend · Q1 (Wk 1–13) · mg/Nm³ vs CPCB limit 450
RAG retrieval pipeline · Research workflow
CO₂ trajectory · 2024 actuals → 2030 forecast ESG
Scope 3 Disclosure · Monte Carlo Reduction Pathways ESG
Probability-weighted Scope 3 reduction pathways · Hover to explore
Monte Carlo 10k runs · Scope 3 Pathways · BRSR FY2024
Net-zero (58%) Conservative (42%) 10k simulations · offset + intensity + audit intervention paths
Sensor Network Topology · Metro Corridor Outages Public Infra
Healthy Drift (>3σ) Outage 15 stations · real Delhi Metro coordinates · click marker for details
GRAP compliance funnel · NCR districts Regulatory
Traffic congestion · DMRC interchange topology Public Infra
Saturated >120% 90–120% Within capacity 12 interchanges · ₹47 Cr remediation
Citation network · ML/AI cluster topology Research
ML Theory NLP/RAG CV/Multimodal 35 nodes · 52 edges · 5 clusters
RAG Evaluation Framework · 3 frameworks compared Research
RAGAS TruLens DeepEval faithfulness · context recall · answer relevancy
Waterlogging · monsoon drainage hotspots · Delhi NCR Public Infra
>30 min standing 10–30 min <10 min 15 blackspots · 9-cm rainfall threshold · Jul–Oct 2024 · click marker for details
Supply Chain Resilience · SPoF Risk Network Industries
High risk (SPoF) Medium risk Low risk 5 critical SPoFs · Rajasthan Coal & Mundra Port highest
NCR Emission Hotspot · 25 BRSR-listed facilities Industries
Speed km/h35
Direction °198°
Steel/Cement (breach) Power/Petrochems Auto/Electronics 47 hotspot zones · plume trails with wind
Facility Energy Intensity · BRSR Peer Benchmarking Industries
GJ / ₹Cr revenue — vs sector peer median (dashed)
Renewable %
Above peer median Below peer median 18 facilities · 7 NIC sectors
Climate Physical Risk · 8 TCFD-Assessed Assets Industries
Speed km/h60
Direction °120°
High risk (>0.6) Medium (0.4–0.6) Low (<0.4) 8 assets · coastal plume expands with wind speed
Supply Chain · SPoF Vulnerability Ranking Industries
Critical (>80) High (70–80) Moderate 5 SPoFs · Rajasthan Coal Mine score 88
Supply Chain · Transport Mode Volume & SPoF Exposure Industries
2+ SPoFs on mode 1 SPoF No SPoF Road 12,040 kt/yr · Rail 3 SPoFs
Facility Energy Intensity · Efficiency Frontier by Sector Industries
Energy intensity (GJ/₹Cr) vs Renewable % · 18 BRSR-listed facilities
18 BRSR facilities · x = GJ/₹Cr · y = Renewable % · CEA target 25%
Sector Renewable Energy Mix · vs CEA Generation Benchmark Industries
Avg renewable energy % by sector · CEA benchmark 25%
At/above 25% target Below target Only Auto & Chemicals sectors meeting CEA benchmark
Climate Physical Risk · 8 Assets × 6 Hazard Matrix Industries
| Asset | Flood | Heat | Cyclone | Wildfire | Water | Coastal | Composite |
|---|---|---|---|---|---|---|---|
| Odisha Coastal | 0.84 | 0.56 | 0.88 | 0.22 | 0.42 | 0.92 | 0.65 |
| Bengal Paper | 0.88 | 0.62 | 0.72 | 0.16 | 0.48 | 0.76 | 0.63 |
| Gujarat Cement | 0.62 | 0.82 | 0.64 | 0.28 | 0.74 | 0.58 | 0.64 |
| Faridabad Steel | 0.74 | 0.68 | 0.12 | 0.18 | 0.81 | 0.05 | 0.49 |
| Rajasthan Chem | 0.22 | 0.94 | 0.08 | 0.44 | 0.92 | 0.02 | 0.47 |
| Gurgaon Auto | 0.52 | 0.72 | 0.10 | 0.14 | 0.78 | 0.04 | 0.44 |
| Pune Auto | 0.58 | 0.60 | 0.32 | 0.38 | 0.66 | 0.18 | 0.49 |
| Himachal Hydro | 0.42 | 0.38 | 0.04 | 0.62 | 0.28 | 0.02 | 0.30 |
Weights: Flood 22% · Heat 18% · Cyclone 16% · Water 20% · Wildfire 12% · Coastal 12% · Source: IPCC AR6 / SwissRe NatCat
High (>0.70) Medium (0.40–0.70) Low · IPCC AR6 SSP2-4.5 · TCFD weights applied
Climate Risk · Insurance Premium Uplift by Asset Industries
Insurance premium uplift % by asset · TCFD material threshold 20%
≥20% (TCFD material) 12–20% <12% Odisha Coastal Smelter +32% · SwissRe NatCat actuary curve
NCR Flood Exposure · Monsoon Risk Zones by Catchment ESG
Critical (≤5yr return) High (5–10yr) Medium Low 698k properties at risk · click zones for detail · NDMA FY2024
Stubble Burning · Wind-Driven PM₂.₅ Plume Attribution ESG
Wind Speed km/h14
Direction °312°
CAAQMS station (PM₂.₅) Fire cluster 2,847 active fires · 38% NCR PM₂.₅ attribution · drag wind sliders
Urban Heat Island · LST Premium Overlay · Delhi Wards ESG
Grid resolution ~500 m · Landsat-8 Band 10 (100m resampled) · 12 Delhi wards · FY2024
NCR Flood Exposure · Cumulative Damage by Catchment ESG
Properties at risk (000s) · NDMA / Delhi Flood Control FY2024
ImpactMitigationNet
Flood impact Mitigation Net 698k properties at risk · Yamuna main 428k · NDMA FY2024
NCR Flood Priority · Urgency × Impact Action Matrix ESG
CriticalHighMediumLow
Yamuna Main & Hindon Drain: Act Now · 8 zones · bubble = population at risk
Stubble Burning · PM₂.₅ Plume Trend vs Fire Count ESG
NCR PM₂.₅ µg/m³ vs active fire count · Oct–Dec 2024 · CPCB + FIRMS VIIRS
PM₂.₅ µg/m³ Fire count Nov 5 peak 496 µg/m³ · 634 fires · FIRMS VIIRS
Stubble Burning · Source Attribution Flow to Delhi ESG
PunjabHaryanaUP
Punjab 42% Haryana 31% UP 27% Hover paths to highlight · NH-44 dominant corridor · North Delhi +18 µg/m³
Urban Heat Island · Ward Temperature Anomaly vs City Mean ESG
LST anomaly vs NCR city mean (°C) · MODIS Terra Day/Night 2024
Above city mean Below city mean Wazirpur +4.8°C hottest · Sanjay Van –4.1°C coolest
Urban Heat Island · Causal Factor Radar by Zone Type ESG
UHI causal factor intensity (0–100) by zone type · SEAC/NDVI analysis
Industrial Commercial Residential Green Zone Industrial heat + albedo dominate · green zones offset via vegetation
Traffic Congestion · 6 Corridors × 5 Time Slots Public Infra
| Corridor | 06:00 | 09:00 | 12:00 | 17:00 | 21:00 |
|---|---|---|---|---|---|
| NH-44 Panipat–Delhi | 3.2 | 9.1 | 6.4 | 8.8 | 5.2 |
| NH-48 Gurgaon–Delhi | 2.8 | 8.6 | 5.8 | 9.2 | 4.8 |
| NH-9 Ghaziabad | 3.6 | 7.8 | 5.2 | 8.4 | 4.2 |
| Ring Road Inner | 4.1 | 8.2 | 7.1 | 8.9 | 6.4 |
| Outer Ring Road | 2.4 | 7.4 | 5.6 | 7.8 | 4.6 |
| DND Flyway | 2.1 | 8.8 | 6.2 | 8.6 | 5.8 |
Peak 09:00 & 17:00 · V/C ratio · NH-48 worst at 0.96 peak
Level-of-Service Benchmark · V/C Ratio vs LOS-C 0.85 Public Infra
ReferenceLine at 0.85 (HCM LOS-C threshold) · red = saturated corridor
Drainage Capacity Deficit · NCR Stormwater Network Public Infra
Design 2840 ML/day → Actual 1510 ML/day · 47% capacity lost
Drainage Incident Lifecycle · 5-Stage Funnel Public Infra
183 events → 62 resolved (34%) · source: NMCG monitoring FY2024
Delhi Grid Load Profile · 24-Hour Demand vs Renewable Public Infra
Peak demand 6.2 GW at 18:00 · renewable 2.82 GW at 15:00 peak solar
Delhi Power Flow · Generation Mix → End Use Public Infra
Coal 42% · Solar 18% · Total 7,200 MW peak dispatch · NTPC + SLDC FY2024
EPR Plastic Waste Flow · US EPA PRO Scenario Regulatory
Producer obligation Fulfilled Shortfall Click or hover nodes to trace flows · 3 PRO tiers · US EPA EPR scenario
EU Night Noise Events · END Directive Lnight (dB) Regulatory
Lnight >65 dB 60–65 dB <60 dB 15 EU cities · END Directive 2002/49/EC · circle = population · click for details
Hudson River · WWTP Discharge Points · BOD mg/L Regulatory
BOD >10 mg/L 7–10 mg/L <7 mg/L 10 discharge sites · Hudson R. Waterford → Yonkers · NYSDEC FY2024 · click for BOD
US Plastic Recovery Gap · 5 Resin Categories · EPA FY2022 Regulatory
42.8 Mt collected → 6.6 Mt recovered · 15.4% recovery rate · source: EPA Plastics Facts & Figures 2022
Plastic Recovery Rate vs 30% EPA Target · By Resin Type Regulatory
HDPE (29.4%) and PET (26.8%) nearest target · Film and EPS critically below · source: EPA 2022
EU Night Noise Events · Q1 2025 Calendar Regulatory
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Peak: New Year Jan 1 (74 events) · Carnival Feb 28 (58) · source: EEA NOISE Obs.
Lnight Exceedance Above 55 dB WHO Limit · 12 EU Cities Regulatory
Compliant cities (Stockholm, Vienna, Warsaw) below WHO target · 8 cities exceed
Hudson River WWTP · BOD/COD Quarterly Trend 2022–24 Regulatory
NYSDEC secondary treatment standard BOD ≤30 mg/L · Q3 storm-runoff peak · 6 of 10 quarters above standard
Hudson Watershed Flow · Tributaries → Main Stem → Estuary Regulatory
Mohawk R. 42% tributary flow · 3 major tributaries · USGS streamflow FY2024
ML/AI Publication Trends · 2016–2024 · arXiv + Semantic Scholar Research
ML Theory NLP/LLM CV NLP/LLM 38% share in 2024 · 4.2× growth since 2020 · source: arXiv cs.CL
Research Topic Share · Citation Cluster Contribution Research
LLM/RAG 38% · CV 24% · Reinforcement 18% · source: Semantic Scholar citation clusters 2024
Retrieval Precision-Recall · 8 RAG Configurations Research
BM25 Dense Hybrid Hybrid top-k=5 Pareto optimal · BEIR benchmark · F1 peak 0.74
RAGAS Score Decomposition · Pipeline Evaluation Research
Positive contribution Gap to target Faithfulness 0.82 · Context Recall 0.76 · Answer Relevancy 0.88
Model Benchmark · MMLU · HumanEval · HellaSwag Research
MMLU HumanEval HellaSwag GPT-4o leads MMLU (88.7%) · Llama-3 competitive on HumanEval
Model Capability Radar · 4 Models × 6 Dimensions Research
GPT-4o Llama-3 Mistral Gemini Reasoning · Coding · Factuality · RAG · Latency · Safety
Grid reliability · transformer load gauge bank Public Infra
>95% capacity 80–95% <80% 20 utility zones · NYISO / ERCOT / PJM / MISO · peak load factors
MLflow Experiment Log · RAG Pipeline · 42 Runs Research
Best run Candidate Failed Best RAGAS 0.84 · chunk_size=512 · top_k=5 · temperature=0.2
Visualization will load here
Awaiting analysis · sources → reasoning → answer
Introducing DataSense
Your Unified Spatial and Temporal Intelligence Stack
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Decision Assist
Ask questions in plain language and get instant insights, summaries, recommendations, and data explanations powered by contextual AI trained locally on your business datasets.
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Total Users
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Engaged
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Intelligent Segmentation
Automatically group customers, vendors, locations, or accounts based on behavior, risk, value, or patterns to enable targeted strategies, prioritization, and personalized engagement.
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Risk Intel
Evaluate financial, operational, and behavioral risk using dynamic scoring models, anomaly detection, and early warning indicators to support proactive decision-making and exposure control.
Future Trend: High Growth (Q4)
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Predictive Forecasting
Forecast demand, risk, revenue, cashflow, or performance using advanced statistical models that identify trends, seasonality, and uncertainty to support confident planning and strategy.
Correlatingspatialdatawithbusinesssignalstouncoverhiddeninsights,assesscriticalrisksandmodelenvironmental impactenablingcondifdent,sustainable,Net Zerodecisions
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Evaluate locations for new / existing setups & simulate operational models for optimising efficiency
DataSense Time
Forecast and go-back in time to analyse patterns and mitigate potential dammages to operational regions
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Analyse historical data to implement dynamic rulesets for ahead-of-time distress warnings and prevention.
Analytics & Forecasting
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With auto sampling dashboards, analyse and forecast trends, demands and risks to your line of operations
Cliko Suite
Single Channel API and Platform Interface for analyzing a startup's digital journey and offline presence
Clover
A 360-degree research and coursework management ecosystem with efficient task planning and traceability
Our Customers
Our collaboration has been across — Government Entities, Educational Institutions, Private Companies
Commitment to Deadlines
What sets Mind Webs apart is not just their exceptional sense of responsibility, accountability, and commitment to deadlines, but the genuine involvement of their founders throughout the entire journey.
Saloni Kerwal
Founder at The Circles
Reliable and Forward-thinking
Since 2022, We have had the privilege of partnering with Mind Webs Ventures on various national hackathons.
Ayan Ghosh
CEO - Creonimus Technology Solutions LLP
Trusted Technology Partner
I have had the pleasure of working with Mind Webs Ventures for more than eight years, and during this time we have successfully collaborated on a wide range of projects, including UI/UX design, web applications, mobile applications, data analytics, and artificial intelligence solutions well before AI became mainstream with tools like ChatGPT.
Dr. Vidyasagar Potdar
Curtin University
Exceeded Expectations
Mind Webs has become a valuable long-term partner for our business and we highly recommend them.
Valentijn Zwolsman
Downtown Developers & The Configurator
From Company's Desk
Latest information on what is happening across the company - from community event news to case studies
Why Early-Stage Products Should Prioritize Systems, Not Features
In the rush to get something out there, many early-stage startups fall into the seductive trap of building features. It feels productive. But this approach often leads to products that lack quality, struggle to scale, and satisfy users in the long r...
Harnessing Data-Driven Spatial and Temporal Intelligence for Global Weather Insights
Unlocking the potential of AI-driven weather forecasting to address regional challenges and foster sustainable development worldwide
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