Reviewer-proof research stack
- Trust Score + reproducibility bundles
- Rigor Guard v2
- Executed Jupyter notebook per analysis
- MCP server — 35 tools
- Teaching & Thesis module
Statistics · PLS-SEM · Research workspace
Every method your reviewers ask for — with the proof behind every result.
InstaBizIntel puts 300+ statistical analyses, SmartPLS-class PLS-SEM, econometrics, machine learning, qualitative coding and BI dashboards in one browser workspace. An AI Analyst picks and runs the method — and every result comes with a Trust Score, an APA write-up and an executed Python notebook.
- Every feature, 15 daysFull trial, no card needed.
- Free foreverDescriptives, charts & dashboards.
- ₹800 / monthPremium (incl. GST) — waivable for faculty & students.
300+
statistical analyses in 14 families
50
ML operators · 37 models + AutoML
24
chart types with a Format pane
35
MCP tools for ChatGPT & Claude
Internal QA run, September 2026: 280 analyses tested, 0 failures — with results matching published reference values for Weibull, Fisher exact, ANOVA, DerSimonian–Laird meta-analysis and logistic regression.
CSV / TSV
Excel (XLSX · XLS · ODS)
SPSS .sav
SAS .sas7bdat
Stata .dta
Parquet
JSON / XML
SQLite
PostgreSQL
MySQL
SQL Server
MongoDB
ODBC · REST · OData
S3 · Azure Blob · B2
Google Sheets
World Bank
FRED
OWID
WHO GHO
SEC EDGAR
ClinicalTrials.gov
GDELT
Yahoo & Binance market data
Audio & video transcripts
RIS / BibTeX
What's new since September
One theme in every release: research that survives review.
InstaBizIntel now lives at instabizintel.instadatahelp.com, and the release log has been busy. The highlights:
Chart Format pane
- Power BI-style formatting
- 15 colour palettes
- Across all 24 chart types
Finance Lab + Prophet
- New Finance Lab module
- Credit-risk tab (Vasicek, credit VaR)
- Prophet in the Forecasting Lab
- Interactive shared dashboards
Data Stories
- Presenter mode
- PDF, PNG & PPTX export
- Data model + schema diagram
- Tableau / Power BI filter set
Maps
- India states map
- Bubble maps
- Flow maps
PROCESS, CB-SEM, NCA & MASEM
- Hayes PROCESS macro — all 76 models
- Full CB-SEM report from lavaan syntax
- Necessary Condition Analysis + cIPMA
- Meta-analytic SEM (MASEM)
- Checked against lavaan, metaSEM & the NCA R package
300+ analyses · 14 families
Pick a family. Every method is point-and-click.
The Statistics Workbench covers the ground of SPSS, Stata, EViews and JMP — and every result carries the same evidence trail, whichever family it comes from.
Descriptive
SPSS-classSummaries and distributions for every variable, each with an automatic chart. Descriptive statistics, data import, charts and dashboards stay free after the trial.
Descriptive statisticsDistributionsAuto-generated charts
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Compare groups
SPSS-classTest whether groups differ — parametric and non-parametric — with effect sizes and an APA-7 paragraph ready to paste.
t-testsANOVAANCOVAMANOVANon-parametric testsFisher exact test
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Correlation
SPSS-classMeasure how variables move together and see it charted, with the same Trust pill and write-up as every other result.
Correlation analysesAssociation measuresVisual output
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Regression
SPSS · Stata-classFrom linear and logistic models to count, quantile, instrumental-variable and survival regression — plus Stata-style panel estimators.
LinearLogisticGLMCount modelsQuantileIVPanel FE / RE + HausmanDynamic-panel GMM
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Multivariate
SPSS · SAS-classFactor analysis, reliability and clustering for your scales, plus configurational methods: fsQCA and Necessary Condition Analysis, which shows whether a factor is a must-have for an outcome, with ceiling plots and bottleneck tables.
Factor analysisReliability (Cronbach α)MANOVAfsQCANecessary Condition Analysis
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
SEM
AMOS · lavaan-classCovariance-based SEM written in lavaan syntax, with global fit (CFI, TLI, RMSEA with its confidence interval, SRMR), loadings and paths, R², indirect effects with confidence intervals, CR, AVE, HTMT and modification indices. CFA sits alongside, and meta-analytic SEM tests a path model on correlation matrices pooled across published studies.
CB-SEM (lavaan syntax)CFAIndirect effects with CIsModification indicesMASEM (two-stage TSSEM)
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Mediation & moderation
SPSS PROCESS-classThe full Hayes PROCESS macro: all 76 models, from simple and serial mediation to moderated mediation with several moderators, with bootstrap confidence intervals, Johnson–Neyman regions and the index of moderated mediation. Binary outcomes are handled with logistic regression, as in PROCESS.
PROCESS models 1–76Parallel & serial mediationModerated mediationJohnson–NeymanIndex of moderated mediationBootstrap CIs
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Causal
Research-gradeA causal DAG estimator with refutation tests and E-values, skeleton discovery, and modern quasi-experimental designs.
Causal DAG estimatorRefutations + E-valueSkeleton discoveryStaggered DiDTarget-trial emulation
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Consumer / market research
SPSS · SmartPLS-classMethods for marketing, HR and management surveys — pairs with IPMA in PLS-SEM and the TAM, UTAUT and SERVQUAL templates.
Survey analysesIPMAModel templatesCareless-response screen
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Time series
EViews-classEViews-style econometrics: stationarity, systems of equations and volatility — up to spillover and wavelet methods.
Unit rootsARIMAETSSTLVARVECMARCH / GARCH / EGARCH / GJRSVARDiebold–YilmazWavelet coherence
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
DOE / SPC
JMP-classStatistical process control and design of experiments, plus statistical sampling for audit work.
SPCDesign of experimentsBernoulli / Poisson samplingHorvitz–Thompson audit sampling
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Survival / clinical
SAS · JMP-classTime-to-event analysis and pharmaceutical methods for clinical and pharmacy research.
Survival analysisSurvival regressionPK-NCADissolution f2
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Reliability
JMP-classLife-data and reliability analysis — Weibull results matched published JMP values in our QA benchmark.
Weibull analysisLife-data methods
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Bayesian
Research-gradeBayesian estimation by MCMC, all the way up to Bayesian structural equation models.
Bayesian MCMCBayesian SEM
Trust pillVerifyBundleRobustnessAPA write-upVisualizeAdd to report
Frontier methods, point-and-click
Download the 272-page analysis guide (PDF) →
PROCESS (Hayes 1–76)MASEMNCA + cIPMAfsQCANetwork meta-analysisWavelet coherenceDynamic-panel GMMStaggered DiDDEA / SFABayesian SEMTarget-trial emulationPK-NCADissolution f2SVARDiebold–Yilmaz
PLS-SEM, SmartPLS-class — and beyond
Your questionnaire to a publishable model — online.
Draw constructs on a drag-and-drop canvas, connect your hypotheses and estimate. Then run every assessment reviewers expect, re-estimate the same model with CB-SEM or Bayesian SEM, and export the syntax to lavaan or Mplus so anyone can check your work.
Measurement modelReflective & formative · loadings, Cronbach α, CR, ρA, AVE, Fornell–Larcker, HTMT, VIF
Structural modelβ, R² / adjusted R², f², SRMR · Path, Factor & Centroid weighting
SignificanceBootstrapping with t, p and confidence intervals (BCa)
PredictionBlindfolding Q², PLSpredict, CVPAT
Groups & prioritiesIPMA, MGA, MICOM, moderation, mediation with specific indirect effects
cIPMAIPMA combined with NCA: which drivers are must-haves for a target level, and how many cases fall short
Advanced proceduresPLSc, NCA, CTA-PLS, higher-order constructs, copula endogeneity, quadratic effects
CB-SEM & Bayesian SEMRe-estimate the same model covariance-based (fit, indirect effects, validity, modification indices) or Bayesian by MCMC
HeterogeneityFIMIX, PLS-POS and REBUS segmentation
Reviewer batteryEvery check mapped to the Hair et al. checklist
InteroperabilityExport lavaan, Mplus or seminr syntax; import lavaan or SmartPLS-style CSV
Reviewer batteryillustrative
Coming from SmartPLS? Bring your model — and get the rest of the workflow.
Every PLS-SEM procedure on the left runs in InstaBizIntel, in the browser on Windows, macOS or Linux. The right column is what the same workspace adds around your model.
| PLS-SEM procedure | InstaBizIntel | Also in the same workspace |
|---|---|---|
| Reflective & formative measurement models | ✔ | 300+ statistical analyses on the same dataset |
| Bootstrapping with confidence intervals | ✔ | Trust Score, audit hash and Inspector re-derivation |
| HTMT, Fornell–Larcker, VIF, R², f², Q² | ✔ | Reviewer battery mapped to the Hair et al. checklist |
| PLSpredict & CVPAT | ✔ | Executed Jupyter notebook + PDF for every analysis |
| IPMA, cIPMA, MGA & MICOM | ✔ | lavaan, Mplus & seminr syntax export; lavaan import |
| PLSc, NCA, CTA-PLS, higher-order constructs | ✔ | AI Analyst interpretation and APA-7 write-up |
| CB-SEM, FIMIX, PLS-POS, copula endogeneity | ✔ | Bayesian SEM by MCMC |
| Printable model report (14 tabs) | ✔ | Qualitative coding, dashboards and Word / PDF reports |
This table lists InstaBizIntel's own capabilities from its user manual (October 2026). It makes no claim about which features SmartPLS does or does not offer — see the vendor's documentation for that. SmartPLS is a trademark of its owner.
Rigor Guard v2 · Trust Score
Every result arrives with its own audit trail.
Each run is hashed (SHA-256) and scored. The Inspector re-derives the numbers independently, Rigor Guard checks your reporting, and one click packages everything a reviewer — or your future self — needs to reproduce it.
- ✔statcheck / GRIM, a citation verifier and an overclaim linter
- ✔Method advisor, robustness battery and APA-7 write-up
- ✔Executable preregistration and multiverse analysis
- ✔Hypothesis tournament and a publication gate
- ✔Reproducibility bundle: RO-Crate, CITATION.cff, reproduce.py, Zenodo DOI
- ✔An executed Jupyter notebook — plus .py, HTML and PDF — for every analysis
AI Analyst · InstaGenie
An AI that runs the analysis — and shows its working.
The AI Analyst takes a request end to end: it pulls the data, chooses and runs the method, and writes the report. InstaGenie sits on every page (⌘J), knows what you are looking at, and accepts datasets, images, PDFs and Word files.
- ✔Ask by typing or hold-to-talk voice
- ✔Plan-first or Auto mode, with a prompt queue
- ✔20 languages, 4 personas, memory, Deep Research
- ✔Every generated SQL query shown and logged
- ✔Charts and dashboards saved only on your approval
- ✔Any LLM provider — 14 presets, incl. InstaRoute
Drive it from ChatGPT or Claude
A 35-tool MCP server, a personal API token, a CLI and an A2A agent card let your own AI assistant run InstaBizIntel analyses.
ChatGPTClaudeClaude Desktop / CodeCursorCodex
What leaves the server: only your question and dataset summaries go to the LLM provider you choose. The statistics, ML and PLS-SEM themselves run on InstaBizIntel's servers. Model routing can go through InstaRoute, our LLM router.
AI Analystillustrative
Does training explain the difference in sales performance across our three regions? Write it up for my thesis.
Here's my plan — approve and I'll run it:
- Check assumptions
- ANCOVA: region, controlling for training hours
- Robustness battery + Trust Score
- APA-7 paragraph and a chart for Chapter 4
SELECT region, training_hours, sales FROM survey_2026;
Done. The result, effect size and APA write-up are in your report, and the notebook is attached. Save the chart to your dashboard?
One workspace, every module
Machine learning to meta-analysis — on the same data.
Import once, then move between modules without exporting a thing.
Visual canvas · no code
Machine learning
A visual node canvas with 50 operators and 37 models — linear models through XGBoost and LightGBM, neural networks, SVM, clustering, Isolation Forest and Optimize. Auto Model builds a leaderboard of up to 8 models plus a top-3 blender, with a leakage screen and 5-fold cross-validation.
Instant baselineSHAPPermutation importancePartial dependenceLeakage screen
Classical to foundation models
Forecasting Lab
Decomposition hybrids (CEEMDAN, VMD, EMD, wavelet) and a model pool from ARIMA, ETS and Theta to N-BEATS, N-HiTS, TiDE, PatchTST, Chronos and TimesFM — and now Prophet. Benchmark with Diebold–Mariano tests and the Model Confidence Set.
Optuna tuningAuto-ensembleConformal intervals.docx publication report
Forecast · auto-ensemble · illustrative
NVivo-class coding
Qualitative
Code documents, media and transcripts by hand, or auto-code by sentiment, topic, pattern or AI themes. Memos, cases, concept maps and team merge, with 16 query tabs including KWIC, word tree, matrix, co-occurrence and saturation.
Cohen κKrippendorff αJoint displayREFI-QDA (.qdpx) export
Transcript · interview 07 · illustrative
From search to forest plot
Lit review & meta-analysis
Search Crossref, OpenAlex, arXiv, Semantic Scholar, PubMed, Europe PMC, DOAJ and Google Scholar; build a PRISMA 2020 diagram; appraise with MMAT, RoB 2, ROBINS-I, NOS, AMSTAR-2 and GRADE; then pool the evidence.
Living reviewsForest & funnel plotsEgger · trim-and-fillMeta-regression8 citation styles
Forest plot · random effects · illustrative
New · 29 Sep 2026
Finance Lab
Performance and risk, portfolio optimisation (max-Sharpe, min-variance, risk parity, efficient frontier, back-test), technicals, news sentiment, EDGAR fundamentals with DCF, filings Q&A and event studies.
Credit VaRVasicek modelAI briefResearch note (.docx)
Portfolio optimisation · illustrative
Power BI-style dashboards
BI & Data Stories
Cross-filtering dashboards across 24 chart types, a Format pane with 15 palettes, India states, bubble and flow maps, and Data Stories with presenter mode — exported to PDF, PNG or PPTX.
Public share linksVersion historyAsk DataSQL editorAlerts & morning briefs
How it works
From a raw CSV to a thesis-ready report.
Six steps, one workspace. Click a step, or let it play.
Bring in anything
CSV, Excel, SPSS, SAS and Stata files, live databases, cloud storage or open data such as World Bank and FRED. No data yet? Start from the 15-dataset sample library.
Clean without code
25 Power-Query-style transform steps, a careless-response screen for survey data, and a synthetic twin (Gaussian copula) when you cannot share the real data.
Pick a method — or ask
Choose from 300+ analyses, draw a PLS-SEM model, or let the AI Analyst and the method advisor pick the right test for your question.
Prove it holds
Trust Score, Inspector re-derivation, robustness battery and Rigor Guard checks — before a reviewer ever sees it.
Report it
APA-7 write-ups, a block-based report builder (cover, AI text, charts, PLS diagram, results) and Data Stories — exported to Word, PDF or PPTX.
Hand over the proof
An executed Jupyter notebook for every analysis and a reproducibility bundle with RO-Crate, CITATION.cff, reproduce.py and a Zenodo DOI.
Teaching & Thesis
Built for the people who teach and examine research.
Start from a ready-made model template, size your sample before you collect a single response, and follow a thesis pipeline that runs from proposal to Chapter 4 and on to the viva. Instructors get a process log of how each student reached their result; students get a Socratic tutor that asks rather than answers.
Model templates
TAMUTAUTUTAUT2TPBSERVQUALECMD&M
Thesis pipeline
Proposal
Data
Analysis
Chapter 4
Viva
PLS sample-size calculatorbefore data collection
Careless-response screenbefore analysis
PhD scholars
Management, commerce, economics, marketing, HR and pharmacy researchers running survey and PLS-SEM studies.
Faculty & supervisors
Teach methods with templates and a tutor, review students’ process logs, and publish your own work. Premium fee waivable.
B-schools & universities
Department plans with multiple seats, deployment on your own server, training and curriculum templates.
Research & analytics teams
Consulting teams and research centres that need publication-grade statistics — and the dashboards to present them.
Tested, not just claimed
280 analyses through QA. Zero failures.
Our internal QA report (September 2026) ran 280 analyses end to end: 231 passed, 49 were validated, and none failed. Benchmark checks matched published reference values for Weibull (JMP), Fisher exact (R / SPSS), ANOVA, DerSimonian–Laird meta-analysis and logistic regression.
The October 2026 additions were checked the same way, against reference software on published example data: CB-SEM fit indices match lavaan, NCA effect sizes and bottleneck tables match the NCA R package, MASEM matches the metaSEM package, and PROCESS coefficients and indirect effects match an independent PROCESS implementation.
Under the hood are well-known open-source statistics libraries — statsmodels, lifelines, scipy, pingouin and semopy — which is also why every result can be exported as plain Python.
Live webinar · InstaBizConnect · 12 Sep 2026
Turn your questionnaire into a publishable model in 30 minutes
A five-construct PLS-SEM model on a 320-response dataset, run live with the AI interpretation written up on screen.
Ask us for the recording on WhatsApp →
Pricing in rupees
Try everything. Keep the basics free.
Every new account starts a 15-day free trial of the full platform — no card needed. After that, choose what you need.
Free trial
₹0 for 15 days
- ✔Every module, every analysis
- ✔PLS-SEM, ML, qualitative, AI Analyst
- ✔No card needed
Free
₹0 forever
- ✔Descriptive statistics
- ✔Data import & sample data
- ✔Charts & dashboards
- ✔The full manual
Full research suite
Premium
₹800 / month
- ✔All 300+ analyses & PLS-SEM
- ✔ML, forecasting, qualitative, Finance Lab
- ✔Maps & AI Analyst
- ✔30 days per payment, via PayU
- ✔Price includes 18% GST · GST invoice
Department
Custom quote
- ✔Multiple seats
- ✔Deployed on your own server
- ✔Training & support
- ✔Curriculum templates
Faculty or student? The ₹800 Premium fee is waivable for faculty and students — ask us about a waiver →
What do I keep after the trial?
Free forever: the basics stay open, no payment needed.
- Data import & 15 sample datasetsIncluded
- Descriptive statisticsIncluded
- Charts & dashboardsIncluded
- The full manualIncluded
- Inferential statistics (300+ analyses)Premium
- PLS-SEM, CB-SEM & Bayesian SEMPremium
- Machine learning & Auto ModelPremium
- Forecasting LabPremium
- Qualitative codingPremium
- Finance LabPremium
- MapsPremium
- AI AnalystPremium
During the 15-day trial everything above is unlocked. Afterwards, inferential statistics, ML, forecasting, PLS-SEM, qualitative and the other premium modules need Premium.
Frequently asked questions
Is there an affordable alternative to SPSS for statistical analysis?
Yes. InstaBizIntel runs 300+ statistical analyses in your browser — group comparisons, regression, factor analysis, time series, survival, Bayesian methods and more — each with a chart, an APA-7 write-up and a Trust Score. Every account gets a 15-day free trial of the full platform; descriptive statistics, charts and dashboards stay free afterwards, and Premium is ₹800 a month.
Can I run PLS-SEM online as an alternative to SmartPLS?
Yes. InstaBizIntel offers SmartPLS-class PLS-SEM in the browser: reflective and formative measurement, bootstrapping with BCa intervals, HTMT, PLSpredict, CVPAT, IPMA, MGA, MICOM, PLSc, NCA, CTA-PLS and higher-order constructs. It can also re-estimate a model with CB-SEM or Bayesian SEM, run FIMIX, PLS-POS and REBUS, map every check to the Hair et al. checklist and export lavaan, Mplus or seminr syntax.
Can I run Hayes PROCESS models, CB-SEM or meta-analytic SEM without SPSS or AMOS?
Yes. InstaBizIntel includes the full Hayes PROCESS macro (all 76 models, with bootstrap confidence intervals, Johnson–Neyman regions and the index of moderated mediation), covariance-based SEM written in lavaan syntax with fit indices, indirect effects and modification indices, Necessary Condition Analysis, cIPMA in the PLS-SEM module, and meta-analytic SEM that pools correlation matrices across published studies. These methods were checked against lavaan, the metaSEM and NCA R packages and an independent PROCESS implementation.
Does InstaBizIntel cover what I use Stata, EViews, JMP or NVivo for?
It covers the core workflows in one workspace: Stata-style panel data (fixed and random effects, Hausman, dynamic-panel GMM), EViews-style time-series econometrics (unit roots, VAR, VECM, the GARCH family), JMP-style SPC, design of experiments and reliability, NVivo-class qualitative coding with REFI-QDA export, Power BI- and Tableau-style dashboards, and a literature-review module with PRISMA 2020 diagrams and VOSviewer-style clusters.
What is the AI Analyst, and do I need to know R or Python?
No coding is needed. The AI Analyst takes a request in plain language or by voice, chooses and runs the method and writes the report; InstaGenie is available on every page for quick questions. You can still see everything: generated SQL is shown and logged, charts are saved only on your approval, and every analysis can be exported as an executed Jupyter notebook.
How much does InstaBizIntel cost?
Every new account gets a 15-day free trial of the full platform, no card needed. After that, data import, descriptive statistics, charts and dashboards stay free. Premium — inferential statistics, PLS-SEM, ML, forecasting, qualitative and the other premium modules — is ₹800 per month including GST (30 days per payment, processed by PayU), and the fee is waivable for faculty and students. Department plans are quoted on request.
Where is my data stored, and what is sent to AI providers?
InstaBizIntel is a hosted service: your uploads are stored on InstaDataHelp servers and may be kept in encrypted cloud storage. The statistics, ML and PLS-SEM run on InstaBizIntel’s own servers. When you use the AI features, only your question and dataset summaries are sent to the LLM provider you have chosen. Departments that need a private set-up can ask for a deployment on their own server.
Can reviewers reproduce my results?
Yes. Every run is hashed and given a Trust Score, the Inspector re-derives results independently, and you can export an executed Jupyter notebook (plus .py, HTML and PDF) for each analysis, or a full reproducibility bundle with RO-Crate metadata, CITATION.cff, reproduce.py and a Zenodo DOI.
Can I use InstaBizIntel from ChatGPT or Claude?
Yes. InstaBizIntel has a 35-tool MCP server that works with ChatGPT, Claude, Claude Desktop and Claude Code, Cursor and Codex, plus a personal API token, a CLI and an A2A agent card.
Which file formats can I import?
CSV and TSV, Excel and ODS workbooks (multi-sheet), SPSS (.sav, .zsav, .por), SAS (.sas7bdat, .xpt), Stata (.dta), Parquet, JSON, XML and SQLite — plus live connections to PostgreSQL, MySQL, SQL Server, MongoDB, ODBC, REST and OData, cloud storage, Google Sheets and open data such as World Bank, FRED, WHO and SEC EDGAR.
Is there a plan for my department or university?
Yes. Department plans include multiple seats, deployment on your own server, training and support, and curriculum templates. Pricing is custom — contact us with the number of users and we will send a quote.
Run your first reviewer-proof analysis today
Import your data, pick a method or ask the AI Analyst, and walk away with the result, the write-up and the notebook. Every feature free for 15 days — no card needed.
instabizintel.instadatahelp.com · contact us
