Run research end to end.
Not just the study.
PulseLake gives researchers one operating system to frame questions, conduct human or AI-native research, deploy agents, analyze evidence, preserve institutional knowledge, automate workflows and deliver decision-ready outputs.
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Research Design
Business question, hypotheses, methods, audiences and instruments.
Create Evidence.
Human, AI-led, synthetic and simulated research in one environment.
Understand
Quant, qual, deterministic calculations and AI-assisted synthesis.
Institutional Memory.
Study context, deep research, cross-study search and knowledge graph.
Client Experience.
Dashboards, reports, presentations, portals and research Q&A.
Operationalize
Workflows, monitoring, scheduled updates and downstream action.
Expert support is included in everything you pay.
Software is getting cheaper, so what you’re really paying for is the expertise. It’s included in every subscription and every bill.
Every way researchers create evidence.
Traditional research remains essential. PulseLake extends it with AI-led interviewing, synthetic research and simulation — while keeping every method inside one governed study context. Four research modes follow: traditional research, AI-led interviews, synthetic research and simulation.
Run rigorous research without losing the context around it.
Design the study, recruit participants, collect evidence, analyze the results and deliver outputs while keeping the objective, methodology, evidence and decisions tied to the same study.
Running maturity assessments? See how PulseLake scores, benchmarks and reuses them →
- 01.
Frame
Capture the decision, hypotheses, research objectives and audience.
Study context - 02
Design
Use reusable questionnaires, assessments, advanced methods and templates.
Research design - 03
Collect
Use panels, owned audiences, qual and multimodal evidence.
Observed evidence - 04
Analyze & deliver.
Quant, qual, NL analysis, dashboards, reports and client outputs.
Decision output
Let AI conduct the interview. Keep the human evidence.
Use conversational or avatar-based interviewers that follow the protocol, probe adaptively and turn every conversation into structured research evidence.
- 01
Define protocol
Set research topics, required questions, rules and guardrails.
Interview design - 02
Conduct
AI or avatar interviews real participants conversationally.
Human evidence - 03
Structure
Transcripts, question paths, themes and metadata become analysis-ready.
Structured qual - 04
Integrate
Evidence becomes part of the same study context as every other method.
Unified context
Explore quickly without pretending generated evidence is observed evidence.
Build explicit synthetic personas and populations to test instruments, explore concepts, compare scenarios and identify what deserves real-world validation.
- 01
Define population
Specify characteristics, assumptions, constraints and intended research use.
Population model - 02
Generate
Create versioned synthetic personas or respondent populations.
Synthetic cohort - 03
Test
Run concepts, instruments, messages or hypotheses against the cohort.
Generated evidence - 04
Validate
Move the most important questions into human research when needed.
Validation plan
Move from “what do people say?” to “what could happen if…?”
Use existing evidence, explicit assumptions, agent interactions and scenario models to explore alternative futures and identify what should be tested next.
- 01
Ground
Bring prior studies and current research context into the model.
Evidence baseline - 02
Define scenario.
Set assumptions, actors, changed conditions and constraints.
Scenario model - 03
Run & compare.
Simulate possible outcomes across alternative conditions or agents.
Simulated outcome - 04
Feed the next study.
Turn uncertainty into targeted hypotheses for further research.
Learning loop
Because the work starts before fieldwork — and continues long after it.
PulseLake connects the execution layer, the intelligence layer and the delivery layer. Research methods are part of the system, not the whole system. Three layers carry the work: run research, understand everything you know, and turn insight into something people use.
Run research.
- Study design & templates
- Human panels & owned audiences.
- AI / avatar interviewing
- Synthetic research.
- Simulation
- Assessments & advanced methods.
Understand everything you know.
- Persistent study context
- Research knowledge graph.
- Cross-study search & deep research.
- Natural language → insight
- Evidence provenance.
- Research agents
Turn insight into something people use.
- Dashboards & interactive analysis
- Automated PowerPoint & reporting.
- Client workspaces & portals
- Research Q&A experiences.
- Scheduled monitoring
- Downstream workflows & actions.
Deploy specialized agents for design, interviewing, analysis, deep research, reporting and client Q&A.
Connect approvals, QA, recurring studies, reporting, notifications and downstream actions into repeatable flows.
Package studies, methods, agents, dashboards and simulations into reusable launchable solutions.
Keep research concepts, entities, measures and relationships structured so intelligence can accumulate cleanly.
Control access, methods, review steps and usage so research remains trustworthy and enterprise-ready.
Trace every answer back to its questions, evidence, transformations, calculations and study context.
Turn your best methods, assessments, templates, workflows and models into scalable assets.
Ask everything your research organization knows.
PulseLake combines study memory, cross-study search, deep research, a knowledge graph and deterministic analysis so users can reason across the entire research estate. Five capabilities work together: study memory, cross-study search, deep research, a knowledge graph and deterministic analysis.
Evidence spans surveys, AI interviews, prior client work and two scenario models. PulseLake synthesizes the answer while retaining citations and evidence type.
Population and filters are resolved from the question; the result is computed against study data rather than generated by the LLM.
Findings, concepts, audiences, measures and decisions are retained so future research can start from what is already known.
The user sees the synthesis together with the underlying studies and evidence types.
Give every researcher an AI team.
Agents work across the operating system. Researchers retain the judgment, approvals and client accountability that require human expertise. Four agents are shown here: Research Designer, Qual Analyst, Deep Researcher and Report Builder.
- Working
Research Designer
Drafts research plans, instruments, methods and initial hypotheses from the study brief.
Drafting concept-test design - Working
Qual Analyst.
Codes interviews, clusters themes, retrieves supporting evidence and surfaces contradictions.
Coding 438 excerpts - Working
Deep Researcher.
Searches across studies, files, findings and organizational knowledge with source-grounded synthesis.
Reviewing 17 prior studies - Waiting.
Report Builder
Turns approved findings into executive narratives, dashboards and client-ready presentations.
Waiting for researcher approval
Reuse what works. Scale what makes you different.
PulseLake lets teams publish proven research assets into reusable team or client experiences — so methodology, automation and intellectual property do not need to be rebuilt for every engagement. Six kinds of asset can be published: studies and assessments, agents and tools, dashboards and reporting, workflows, methods and frameworks, and ontology and knowledge.
-
Research solutions
Studies & Assessments.
Reusable study frameworks, assessments, questionnaires and proven research designs that can be configured and launched again.
Reuse solution -
AI capability
Agents & Tools.
Publish research agents and specialized tools for design, coding, analysis, synthesis, reporting and client support.
Add capability -
Delivery assets
Dashboards & Reporting.
Reuse dashboards, report structures and presentation outputs instead of rebuilding delivery for each study or client.
Reuse output -
Operations
Workflows
Standardize approvals, QA, recurring studies, notifications, analysis and delivery through reusable automated workflows.
Reuse workflow -
Research IP
Methods & Frameworks.
Preserve questions, scoring logic, benchmarks, methodologies and proprietary frameworks as reusable organizational assets.
Reuse IP -
Shared intelligence
Ontology & Knowledge.
Reuse common dimensions, measures, concepts and research structures so programs remain comparable and connected over time.
Extend knowledge
Turn findings into an ongoing intelligence experience.
The point is simple: PulseLake does not stop after analysis. Approved findings can become dashboards, automated presentations, client workspaces, AI Q&A, scheduled monitoring and downstream actions — without rebuilding the research context each time.
Evidence, analysis and conclusions are reviewed and finalized.
The same research becomes interactive and presentation-ready outputs.
Clients access a persistent branded environment instead of a one-time attachment.
Users ask questions against the approved study context and underlying evidence.
Schedule updates, trigger workflows and keep the insight alive after delivery.
Questions about PulseLake, answered.
Short, direct answers from the full FAQ. Planning a survey? Try the free sample size and significance calculators.
What is PulseLake?
PulseLake is an AI-native operating system for market research and insight professionals. It gives researchers one system to frame questions, conduct human or AI-native research, deploy agents, analyze evidence, preserve institutional knowledge, automate workflows and deliver decision-ready outputs.
Who is PulseLake for?
PulseLake is built for internal insights teams, market research firms and consulting practices: the people who design studies, generate evidence and turn it into decisions for their organizations or their clients.
How is PulseLake different from a survey or research tool?
Most research tools help run a single study. PulseLake runs the research system around it: an execution layer for running research, an intelligence layer for understanding everything the organization knows, and a delivery layer for turning insight into something people use, all sharing one persistent study context.
What kinds of research can you run in PulseLake?
PulseLake supports four research modes. Traditional research covers surveys, qualitative research, assessments, panels and advanced methods. AI-led interviews run conversations with real participants. Synthetic research uses explicit, versioned personas and populations. Simulation explores scenarios grounded in prior evidence and explicit assumptions.
Conduct the research. Deploy the agents. Preserve the knowledge. Run the operation.
PulseLake turns a fragmented research stack into one AI-native operating system for researchers, insights teams and research firms. Three audiences are served: researchers, insights teams and research firms.