You see only what you're cleared to
Every retrieval respects source permissions. The same question can produce different answers for different people.
Knowledge
Everything your brand knows, and everything it doesn't yet, in one place
Merciv unifies your internal data, external signals, syndicated research, and our own consumer datasets into one living, connected knowledge base.
30 minutes, your use case, real data. No migration required.
You don't have a data problem. You have a knowledge problem.
Consumer knowledge is scattered across internal files, tools, and the open web. Teams lose hours to retrieval, fall back on assumptions, and make big calls on data that's already out of date.
Generic AI guesses.
It can summarize a file, but it has no persistent memory of your business, no permissions, and no citations. With the wrong context, it answers confidently and wrong.
Internal-only tools are blind to the market.
They tell you what you've already documented. They can't tell you what's happening now, or what it means.
External-only tools are mostly noise.
Social listening shows you a feed. Without your products, research, and strategy as context, signal never becomes a decision.
Static research is already stale.
By the time a study is packaged and circulated, the market has moved. Knowledge that should compound dies in a deck instead.
How it works
Merciv maps the answers before you ask the questions
Merciv connects your sources, structures the corpus, relates entities across silos, and surfaces the answer — so the first query already lands on a trustworthy foundation.
Connect every source
Bring in files, connected systems, syndicated feeds, and live external signals.
Structure the corpus
Messy internal data and live external signals land in domains — organized so agents, models, and humans can actually use them.
Relate across silos
Merciv builds the relationships and context across sources, prioritized by importance — the links keyword search never finds.
Answer from the graph
The answers already live in your knowledge ecosystem. Merciv retrieves the evidence subgraph behind one complete, cited answer.
Merciv connects internal context, external reality, syndicated validation, and our own consumer datasets, so an answer is never missing context.
Sales dataResearch reportsStrategy decksCRM exports
Social conversationsReviews & ratingsNews & forumsCompetitive intel
Panel dataCategory benchmarksRetail & POSMarket share
Structured dataPartner integrationsConsumer panelsCategory signals
Internal
Connect everything your business already knows
The research, decks, spreadsheets, and systems your teams have built up for years — unified into one living source of truth that grounds every answer in your actual context.
Bring in research reports, strategy decks, past studies, and brand guidelines — every file your teams have ever produced.
Connect the systems you already run: Looker, Snowflake, Databricks, SAP, Drive, SharePoint, and more.
Unify sales data, voice-of-customer, reviews, and customer feedback in one system.
Bring data as-is — Merciv cleans it and maps the entities and relationships across all of it to make it usable and useful.
External
Understand your category and consumers in real time
Social conversations, reviews, trends, news, and more — pulled constantly and proactively so your knowledge stays ahead of the market.
Pull in live signal from social, reviews, search, and the open web — TikTok, Reddit, Amazon, Google Trends, and more.
Track what consumers are saying about your brand, your competitors, and your category as it's said.
Catch emerging trends, claims, and complaints as they form, not after they surface in a quarterly report.
Syndicated
Unlock the true value of syndicated data
Bring your syndicated investments into the same system as your internal knowledge and live signal — so you can explain the why behind the what.
Connect Circana, NielsenIQ, Mintel, and your other syndicated and market-research sources.
Anchor your internal knowledge and live signal to validated category and market context.
Move from “what happened in the market” to “why it happened — and what to look at next.”
Your data lands in your isolated tenant, is never used to train models, and stays yours.
Merciv
A head start you don't have to build, from day one
Merciv brings its own structured consumer datasets, so you start with category and competitive context already in place — not a blank knowledge base.
Start with product and variant data, review and sentiment data, and category context out of the box.
Ground your research in precomputed perception signals built across the consumer landscape.
Benchmark your brand against the category without standing up new data pipelines.
Combine it with your internal, external, and syndicated sources for a full picture.
Knowledge graph
Generic AI breaks down at scale. Merciv gets better at scale.
Accurate, cited answers — not a guess from whichever fragment looked closest.
| Capability | Standard RAG | Merciv knowledge graph |
|---|---|---|
| Knowledge model | Documents split into fragments that never connect | Entities and relationships mapped across your library |
| Retrieval | Returns chunks that look most similar to the question | Relationship-aware retrieval, so the right source rises |
| Accuracy at scale | Collapses as files pile up and everything looks alike | Holds across thousands of files — and improves as you grow |
| Citations | Loose or document-level, if any | Page- and paragraph-level, with a full reasoning trail |
| When evidence is thin | Answers confidently anyway | Says so, and flags what's missing |
Answers, not approximations. When a question involves math, Merciv runs actual computation in a sandbox and cites the file — so every figure is correctly calculated.
Cited end to end. Every finding links to its exact source, and every step is logged, showing exactly how Merciv reached any conclusion.
Honest about the gaps. When the evidence isn't there, Merciv says so and flags what's missing instead of inventing an answer.
Built for scale. Merciv reasons across thousands of files, narrowing intelligently before it retrieves, so accuracy holds as you grow.
Plug into the tools you already run
Merciv connects to your warehouse, BI, CRM, storage, and the apps your team lives in. No migration required.
See it on your stack
Permissions
Permission-aware at every step. Privacy is a default, not an add-on.
Knowledge is only safe to centralize if access is enforced as carefully as it's connected. Merciv inherits your existing permissions and applies them to every user, query, and agent.
Agents query knowledge, never raw files
Models reason over structured findings, not underlying systems — so missing permissions never expose unintended data.
Control that follows the output
Permissions extend to citations and evidence. Shared findings never grant access to restricted source material.
Your data, your residency, your exit
Choose where data resides, export it when needed, and receive written confirmation when deletion is complete.
Enterprise
Enterprise-grade security by design. Your knowledge stays yours.
Merciv is built for teams that need AI outputs to be secure, permissioned, and defensible at every layer — so you can connect, upload, and integrate with confidence.
Zero-training by design
Your data lives in a structured knowledge layer, not a training pipeline. Merciv never uses it to train models.
SOC 2 Type II
Security controls are independently audited and continuously reviewed. Infrastructure runs on AWS-certified environments.
Encrypted everywhere
Data is encrypted at rest and in transit, with managed keys, full-disk encryption, and secure media sanitization.
Least-privilege by default
Access is controlled through RBAC, MFA, SSO, and SCIM. Permissions are granted and revoked deliberately.
Tenant-isolated
Every customer environment is logically isolated and encrypted. Your data stays separated from others, always.
Proven and monitored
Independent testing, continuous scanning, and incident monitoring find and mitigate risks quickly.