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The Research Operating System
with mathematically verified questionnaires.

One platform escorts the researcher from ideation to data quality analysis — design, campaign, execution, and analysis coordinated by a central Research Brief, with formal mathematical proof that the questionnaire's logic is sound before you field it.

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Ideate
Design
Campaign
Execute
Analyze
Bonus
Simulate

One platform. The whole research lifecycle.

Four specialized AI agents work from a single, evolving Research Brief — the central source of truth for every project. Ideation, design, campaign, execution, and data quality analysis stay in lockstep, with formal mathematical proof that the questionnaire's logic is sound.

roundtable.dev.askalot.io
Askalot unified research hub — the Round Table navigation linking Armiger, Targetor, SirWay, and Balansor around a central Research Brief

One Brief, Four Agents

A central Research Brief is the source of truth for every project. Designer, Manager, Respondent, and Analyst all read from and write to the same brief, so ideation, design, campaign, execution, and analysis stay coherent end-to-end.

λ

Mathematical Guarantees

Z3 SMT solver formally proves questionnaire logic is sound — every question reachable, every path valid, every contradiction caught before deployment.

Two Ways to Use Askalot

As a SaaS: our Designer, Manager, and Analyst agents are tuned with the Claude Agent SDK — Anthropic API or AWS Bedrock for IAM, VPC, and data-residency. As a tool: plug the 80+ MCP tools into your own agentic harness with any model.

See the full lifecycle

From ideation to data quality analysis.

Five stages, one Research Brief, zero gaps — the full research lifecycle in a single platform.

Armiger

Ideate & Design

Turn a research question and source documents into a Research Brief, then into a QML questionnaire with mathematical proof of logical soundness.

Targetor

Campaign

Target the right audience with AI-powered sampling strategies and demographic distribution.

SirWay

Execute

Execute surveys via magic links, interviewer-assisted interviews (phone & in-person), or AI simulation with persona profiles.

Balansor

Data Quality Analysis

Weight, measure, and defend your dataset — raking, representativeness metrics, straightlining and speeder flags, multi-format export.

armiger.dev.askalot.io
Armiger - the Research Assistant agent producing a structured Research Brief (research goal, measurable metrics, KPIs, target audience) from uploaded research materials

A structured Research Brief with traceable citations back to your source documents

Ideate · Armiger

It starts with an idea — and the documents you already have.

Upload your available materials — research papers, regulations, clinical guidelines, policy documents, prior studies. The Research Assistant agent ingests and semantically indexes them, then collaborates with you to define the research goal, measurable metrics, KPIs, target audience, and questionnaire format — all captured in the Research Brief, the source of truth that travels with the project through every stage.

  • Document ingestion — PDF, Word, spreadsheets, plain text; semantically indexed for retrieval across large sets
  • Collaborative scoping — the agent proposes research goals, measurable constructs, KPIs, target audience, and the questionnaire format; you steer and approve
  • Research Brief — the approved brief becomes the contract every later stage and agent reads from
  • Project isolation — indexed documents are scoped to your project for team-level data separation
Social Research Market Research Risk & Compliance Legal Discovery Critical Systems Healthcare & Triage Clinical Due Diligence
Design · Armiger

From an approved brief to a questionnaire proven sound.

With the Research Brief approved, you or the Designer agent author the questionnaire in QML — conditional logic, skip patterns, and the right response controls. The Z3 SMT solver then mathematically proves there are no circular dependencies, no dead ends, and no contradictions, iterating generate → validate → fix until every path is sound.

  • AI generates QML from natural language or document ingestion
  • Z3 SMT solver validates reachability and logical consistency
  • Iterative refinement loop: generate → validate → fix → re-validate
  • Browser-based IDE with syntax highlighting and flow visualization
  • Support for 8+ research domains (market research, clinical, due diligence, IT security...)
Launch Armiger
armiger.dev.askalot.io
Armiger - QML questionnaire editor with React-Flow flow diagram and live item preview

Z3 SMT Validation Passed

Every item reachable · all postconditions satisfiable · 0 contradictions

targetor.dev.askalot.io
Targetor - Campaign management with sampling strategies, demographic targeting, and quality scoring
targetor.dev.askalot.io
Targetor - AI-assisted sampling strategy configuration with stratification factors and quality scoring
Campaign · Targetor

Target the right audience. Field it in waves.

With the Campaign Manager agent, define a sampling strategy, generate respondent pools with quality scoring, and plan the campaign as a single run or recurrent waves. Targetor generates the actual surveys from the campaign and assigns them to interviewers — via a guided wizard, conversational chat, or the 80+ MCP tools.

  • AI-powered campaign wizard with conversational interface
  • Sampling strategies with demographic distribution factors
  • Greedy and random-constrained pool generation with RMSE quality scoring
  • Campaign management with progress tracking and invitation dispatch
  • Interviewer workload distribution and assignment management

A guided 5-step wizard — or conversational chat for power users

1
Campaign design — name, questionnaire, mode
2
Target audience — demographics, sample size
3
Sampling strategy — stratification factors, distributions
4
Respondent pool — generate and preview quality
5
Review & launch — summary, validation, deployment

Monitor & groom — not just this campaign

Track response rates across every running study, refine a campaign mid-flight, and adjust interviewer assignments or respondent pools as the field evolves — recurrent waves keep collecting against the same strategy.

Launch Targetor
Execute · SirWay

Field surveys with logic that can't contradict itself.

Two execution paths: respondents complete surveys directly via magic links, or interviewers facilitate interviews by phone or in person. SirWay computes each next question lazily from preconditions, so respondents see only what's relevant — and the SMT proof from the design stage guarantees navigation can never contradict itself.

  • Direct mode (magic links) and Interviewer-Assisted mode (phone & in-person)
  • Lazy evaluation: questions computed dynamically from preconditions
  • Contradiction-free navigation guaranteed by SMT validation
  • Backward navigation and progress tracking for respondents
Launch SirWay
sirway.dev.askalot.io
SirWay - Survey execution with lazy evaluation, dynamic question flow, and respondent navigation
balansor.dev.askalot.io
Balansor - Medallion data pipeline with Bronze, Silver, Gold stages, quality metrics, and multi-format export
Analyze · Balansor

Don't just export results. Defend them.

Extract responses from the surveys, QA them, then re-balance with post-stratification raking against the sampling strategy. The medallion architecture refines data (Bronze raw → Silver weighted → Gold publication-ready), and per-stage metrics quantify representativeness, completion, response patterns, and internal consistency. The Analyst agent reads the Research Brief to interpret the dataset against the original objectives, not in isolation.

  • Medallion pipeline: Bronze → Silver → Gold with full lineage
  • Raking algorithm for post-stratification weighting
  • Quality metrics: representativeness (RMSE, χ², max deviation), straightlining, speeder flags, Cronbach's α, design effect
  • Export: CSV, Excel (.xlsx), SPSS (.sav), Parquet
  • Semantic clustering turns open-ended answers into quantitative theme indicators

Open-ended → quantitative

Embeddings group free-text responses by meaning, not keywords, so similar ideas cluster even when worded differently. Choose c-TF-IDF keywords for speed or LLM labels for natural names — each theme becomes a Gold indicator column ready for cross-tabulation and export.

Launch Balansor
roundtable.dev.askalot.io
RoundTable - synthetic respondent simulation with persona-driven, agentic per-question response generation
Bonus · Simulate · Roundtable

Pressure-test the whole project before a single human answers.

Beyond the five-stage lifecycle, Roundtable can simulate an entire research project with synthetic respondents — for validating questionnaire flow, exercising the analysis pipeline, or generating demo datasets. Response generation has multiple levels: lightweight statistical fills for speed, up to the heaviest mode where each respondent is a unique persona and Claude Haiku answers question by question with the persona, demographics, and accumulated Q&A history — so a respondent who said "unemployed" won't describe a workplace later.

Single

One survey, one persona

Campaign

Full 3-phase lifecycle

Mass Fill

Bulk synthetic data

  • Multiple generation levels — from fast statistical fills to agentic per-question responses
  • Three-phase flow: Preparation → Execution → Analysis
  • Exercise the Bronze → Silver → Gold pipeline with synthetic data before fielding
Young Professional Married Family Retired Senior High-Income Executive Random
Launch Roundtable

Use it as a SaaS. Or as a tool in your own agent.

In the hosted SaaS, our Designer, Manager, and Analyst agents are tuned with the Claude Agent SDK — Anthropic API or AWS Bedrock for IAM, VPC, and data-residency. Prefer your own agentic harness? Connect via MCP and bring any model.

A

Anthropic

Claude Sonnet, Claude Haiku

Default provider

O

OpenAI

GPT-4, GPT-4o

Local AI

Ollama, Llama, Mistral

Free — hosted on our servers

G

Google

Gemini Pro, Gemini Ultra

Grounded in peer-reviewed research.

When you ask why, our agents don't guess. They consult a shared library of ~30 peer-reviewed books and papers spanning the full research lifecycle — Dillman, Krosnick, Groves, Tourangeau, Bethlehem, Heeringa, Schouten, Fowler — and cite the paper, year, and passage in their answer.

D

Designer

Validity, reliability, wording, skip patterns.

Taherdoost 2016 · Aithal 2020 · Krosnick 2010 · Fagan & Greenberg 1988 · Feeney 2019

M

Manager

Sampling design, weighting, DEFF, adaptive survey design.

Heeringa 2010 · Bethlehem 2012 · Schouten 2009/2013 · Kish 1965

A

Analyst

Total Survey Error, nonresponse bias, raking, response quality.

Groves et al. · Bethlehem 2004 · Dillman 2014 · Tourangeau 2000

The library is indexed with graph-aware retrieval so an agent can find the exact passage that answers the question you asked, not just the paper that mentions the topic. Agents default to their built-in training for routine questions to keep latency low, and reach for the full corpus when you ask for a citation or when the question sits outside the routine.

80+ tools. One unified API.

Every platform capability is accessible via REST API and Model Context Protocol (MCP). Drop Askalot into Claude Code, Cursor, Claude Desktop, or your own agentic framework — use whichever model you prefer. The full research lifecycle becomes tool calls for your agent.

5 Project Management
5 Questionnaires
9 Campaigns
6 Respondents
8 Pools
6 Strategies
4 Workload
8 Surveys
2 Users
8 Datasets
3 Audit
3 Documentation
MCP Tool Call 
// AI agent creates a campaign via MCP
create_campaign({
  name: "Q1 National Survey",
  project_id: "proj_abc123",
  questionnaire_id: "qst_def456"
})

// Then generates a representative sample
generate_pool_from_strategy({
  strategy_id: "str_ghi789",
  pool_name: "National Sample Q1"
})

Built for research organizations that demand rigor.

Multi-Tenant Isolation

Dedicated environments with custom domains, independent databases, and full resource isolation per organization.

GDPR Compliant

Full audit trails, data processing controls, and respondent consent management built into every workflow.

SOC 2 Type II Coming Soon

Enterprise-grade security controls with continuous monitoring and formal compliance certification.

Role-Based Access

Admin, Designer, Manager, Interviewer — granular permissions at project, campaign, and resource level.

Full Audit Trail

Every action tracked with entity history, actor identification, and time-series event storage for compliance.

Peer-Reviewed Methodology

Agents consult ~30 survey-methodology books and papers across the full research process — Dillman, Krosnick, Groves, Tourangeau, Bethlehem — and cite the passage they used.

SaaS or MCP Tool

Use the hosted SaaS with Claude-tuned agents (Anthropic API or AWS Bedrock), or wire the 80+ MCP tools into your own agent and model of choice.

From research question to defensible data.

One Research Brief, four AI agents, formal mathematical proof of every questionnaire's logic — the full research lifecycle in a single platform.

Create Free Account Quick Start Guide