Run research end to end.
Not just the study.
The AI-native OS for market research & insight professionals.
One operating system for the whole job. Researchers frame the question, run human or AI-native research, deploy agents and analyze the evidence in PulseLake. Then they keep the institutional knowledge, automate the workflows and deliver decision-ready outputs from the same place.
Not sure where to start? Tell us your use case and get free expert help, by chat or email.
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.
Because the work starts before fieldwork. And it continues long after.
Six stages, one study context. Agents do the legwork at every stage. Researchers keep the judgment, the approvals and the client accountability, because those need human expertise.
01 · Frame
Research design.
Turn the business question into a study: the decision, hypotheses, methods, audiences and instruments.
Research Designer drafts the plan, instruments and first hypotheses from your brief.
How it works- When
- At the start, before anyone writes a question.
- How it works
- Start from reusable questionnaires, assessments, advanced methods and templates. The agent drafts. You edit and approve.
- What you get
- A study design tied to the decision it serves, so the context travels with the study from here on.
02 · Research
Create evidence.
Four ways to create evidence in one place: traditional research, AI-led interviews, synthetic research and simulation.
Interview Agent runs conversational or avatar interviews that follow your protocol.
How it works- When
- Whenever you need evidence, observed or modelled.
- How it works
- Surveys, qual, panels and owned audiences. Interviewers that probe adaptively. Explicit synthetic personas to test instruments and concepts. Scenario models for what could happen. Generated evidence is never treated as observed evidence.
- What you get
- Evidence from every method, kept inside one governed study context.
03 · Analyze
Understand
Quant, qual and AI-assisted synthesis. Numbers are calculated against your study data, never generated by the model.
Qual Analyst codes interviews, clusters themes and surfaces contradictions.
How it works- When
- Once evidence starts coming in.
- How it works
- Ask in plain language. Calculation mode resolves the population and filters from the question and computes the answer, with the base shown. Qual is coded, themed and linked back to the excerpts.
- What you get
- Findings you can check: every figure has its base, every theme its evidence.
04 · Know.
Institutional memory
Every study becomes context the next one starts from. Study memory, cross-study search, deep research and a knowledge graph.
Deep Researcher searches studies, files and findings, then writes a synthesis grounded in the sources.
How it works- When
- Before you commission new research, and whenever someone asks what you already know.
- How it works
- Findings, concepts, audiences, measures and decisions are kept. Ask a question and PulseLake pulls in the relevant prior evidence, with citations and evidence types attached.
- What you get
- Answers that draw on the whole research estate, not one project at a time.
05 · Deliver.
Client experience
Approved findings become dashboards, automated PowerPoint, client workspaces and AI Q&A, without rebuilding the context.
Report Builder turns approved findings into narratives, dashboards and presentations, once a researcher signs off.
How it works- When
- When findings are approved and people need to use them.
- How it works
- Package the same research as interactive and presentation-ready outputs. Publish it to a persistent, branded client workspace instead of a one-time attachment. Clients ask questions against the approved study context.
- What you get
- One study, several living outputs, all on the same approved context underneath.
06 · Act
Operationalize
Keep the insight working after delivery: scheduled updates, monitoring and workflows that trigger the next step.
Workflow Agent waits for approval, then runs the next step.
How it works- When
- After delivery, when the research should keep paying off.
- How it works
- Connect approvals, QA, recurring studies, reporting, notifications and downstream actions into repeatable flows.
- What you get
- The next wave scheduled, the team alerted, the client updated, without starting over.
Underneath every stage
- Governance Control access, methods, review steps and usage.
- Lineage Trace every answer back to its questions, evidence, calculations and study context.
- Ontology Concepts, entities, measures and relationships stay structured, so knowledge builds up cleanly.
- Reusable IP Your best methods, templates and workflows, published as assets. See the marketplace ↓
Every way researchers create evidence.
Traditional research still matters. PulseLake adds AI-led interviewing, synthetic research and simulation to it, and keeps every method inside one governed study context. That gives you four research modes, side by side: 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 the outputs. Through all of it, the objective, methodology, evidence and decisions stay 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.
Conversational or avatar-based interviewers follow your protocol and probe adaptively. Every conversation comes back as 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. Use them to test instruments, explore concepts and compare scenarios, and to spot 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…?”
Start from the evidence you already have. Add explicit assumptions, agent interactions and scenario models, explore alternative futures, and find out 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
Ask everything your research organization knows.
Five capabilities work together here: study memory, cross-study search, deep research, a knowledge graph and deterministic analysis. The result? People can reason across the entire research estate instead of one project at a time.
The evidence spans surveys, AI interviews, prior client work and two scenario models. PulseLake synthesizes the answer and keeps the citations and evidence type attached.
Population and filters come from the question itself. The number is computed against study data, not generated by the LLM.
Findings, concepts, audiences, measures and decisions are kept, so future research can start from what is already known.
The user sees the synthesis together with the underlying studies and evidence types.
Reuse what works. Scale what makes you different.
Take the research assets that already work and publish them as reusable experiences for your team or your clients. Methodology, automation and intellectual property then don't need rebuilding 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.
Study frameworks, assessments, questionnaires and research designs that have worked before. Configure them and launch 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
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. In one system, researchers frame questions, conduct human or AI-native research, deploy agents and analyze evidence. It also preserves institutional knowledge, automates workflows and delivers 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. There is 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 three share 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, while 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. Built for researchers, insights teams and research firms.