FAQs
Questions before you go live?
Questions before you go live?
Questions before you go live?
How does Lopus handle data accuracy?
Lopus takes three steps to ensure every answer is accurate. First, the AI asks clarifying questions before writing any SQL, so you know exactly what it's querying. Second, every answer is governed by your semantic layer — Lopus doesn't guess what "revenue" means, it uses the definition you locked in during setup. Third, confidence scoring is built in — when data looks incomplete, stale, or ambiguous, Lopus tells you. Every answer shows its work: the SQL query generated, the tables and fields used, and any assumptions made. Technical users can audit every result. This transparency is a design principle, not an afterthought.
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How does Lopus handle data accuracy?
Lopus takes three steps to ensure every answer is accurate. First, the AI asks clarifying questions before writing any SQL, so you know exactly what it's querying. Second, every answer is governed by your semantic layer — Lopus doesn't guess what "revenue" means, it uses the definition you locked in during setup. Third, confidence scoring is built in — when data looks incomplete, stale, or ambiguous, Lopus tells you. Every answer shows its work: the SQL query generated, the tables and fields used, and any assumptions made. Technical users can audit every result. This transparency is a design principle, not an afterthought.
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Is my data secure with Lopus?
Yes. Lopus is SOC 2 Type 1 compliant and follows enterprise-grade security practices. Your data is completely isolated — your instance, your data, your infrastructure, separated from every other customer. Lopus never uses your business data to train models or improve the product. You control who can query which datasets, who can build dashboards, who can share externally, and who can modify business logic. You can also connect your own data warehouse if you prefer to keep data in your existing infrastructure. Permissioned access controls are enforced at every level.
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Is my data secure with Lopus?
Yes. Lopus is SOC 2 Type 1 compliant and follows enterprise-grade security practices. Your data is completely isolated — your instance, your data, your infrastructure, separated from every other customer. Lopus never uses your business data to train models or improve the product. You control who can query which datasets, who can build dashboards, who can share externally, and who can modify business logic. You can also connect your own data warehouse if you prefer to keep data in your existing infrastructure. Permissioned access controls are enforced at every level.
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How much does Lopus cost?
Lopus pricing starts at $1,999 per month for growth-stage companies, which includes the managed data warehouse, all integrations, the AI Analyst, dashboards, Canary Alerts, and Forward-Deployed Data Engineer setup. Compared to the alternatives — a data analyst hire at $120K–$180K per year, a Looker deployment at $35K–$150K per year plus a data engineer to maintain it, or the hours your team currently spends manually pulling reports — Lopus delivers the same capabilities at a fraction of the cost and time.
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How much does Lopus cost?
Lopus pricing starts at $1,999 per month for growth-stage companies, which includes the managed data warehouse, all integrations, the AI Analyst, dashboards, Canary Alerts, and Forward-Deployed Data Engineer setup. Compared to the alternatives — a data analyst hire at $120K–$180K per year, a Looker deployment at $35K–$150K per year plus a data engineer to maintain it, or the hours your team currently spends manually pulling reports — Lopus delivers the same capabilities at a fraction of the cost and time.
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Can I use Lopus with my existing data warehouse?
Yes. If you already have a Snowflake, BigQuery, or PostgreSQL warehouse, Lopus can connect directly to it. You own your data from day one. If you don't have a warehouse, Lopus provisions and manages one for you as part of the platform. Either way, your Forward-Deployed Data Engineer handles the configuration. You never need to manage data pipelines, transformations, or warehouse maintenance yourself.
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How fast will I get access to my virtual
Yes. If you already have a Snowflake, BigQuery, or PostgreSQL warehouse, Lopus can connect directly to it. You own your data from day one. If you don't have a warehouse, Lopus provisions and manages one for you as part of the platform. Either way, your Forward-Deployed Data Engineer handles the configuration. You never need to manage data pipelines, transformations, or warehouse maintenance yourself.
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What integrations does Lopus support?
Lopus supports 500+ integrations the most common tools in the GTM, revenue, and product stack: CRM: HubSpot, Salesforce, Attio, Pipedrive, Zoho CRM, Microsoft Dynamics 365, Close, Copper, etc. Billing: Stripe, Chargebee, Recurly, Zuora, Recharge, BillingPlatform, Paddle, etc, Product analytics: Mixpanel, PostHog, Amplitude, Heap, Pendo, FullStory, Gainsight PX, etc. Accounting: QuickBooks, NetSuite, Xero, Sage Intacct, FreshBooks, Wave Databases: PostgreSQL, MongoDB, Snowflake, BigQuery, RedShift, MySQL, DuckDB, CockroachDB, AlloyDB, Firestore, DynamoDB Customer Support: Intercom, Zendesk, Freshdesk, Drift, Gorgias, Front Communication: Slack, Microsoft Teams (for alerts and notifications) New integrations are added continuously. If your tool has an API, Lopus can likely connect to it. Your Forward-Deployed Engineer handles all integration setup.
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What integrations does Lopus support?
Lopus supports 500+ integrations the most common tools in the GTM, revenue, and product stack: CRM: HubSpot, Salesforce, Attio, Pipedrive, Zoho CRM, Microsoft Dynamics 365, Close, Copper, etc. Billing: Stripe, Chargebee, Recurly, Zuora, Recharge, BillingPlatform, Paddle, etc, Product analytics: Mixpanel, PostHog, Amplitude, Heap, Pendo, FullStory, Gainsight PX, etc. Accounting: QuickBooks, NetSuite, Xero, Sage Intacct, FreshBooks, Wave Databases: PostgreSQL, MongoDB, Snowflake, BigQuery, RedShift, MySQL, DuckDB, CockroachDB, AlloyDB, Firestore, DynamoDB Customer Support: Intercom, Zendesk, Freshdesk, Drift, Gorgias, Front Communication: Slack, Microsoft Teams (for alerts and notifications) New integrations are added continuously. If your tool has an API, Lopus can likely connect to it. Your Forward-Deployed Engineer handles all integration setup.
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How are Lopus dashboards different?
Traditional dashboards are static - someone on the data team builds them, and you look at the same charts every day. Lopus dashboards are AI-generated, interactive, and disposable. You describe what you want to see in plain English, and Lopus builds the dashboard in seconds. You can drill into any chart, ask follow-up questions, change filters, and explore your data interactively. Build ten dashboards. Build a hundred. Throw them away and build new ones the next day. The cost of creating a dashboard drops to near zero, which means you always have the exact view you need right now — not the one someone built for you last quarter.
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How are Lopus dashboards different?
Traditional dashboards are static - someone on the data team builds them, and you look at the same charts every day. Lopus dashboards are AI-generated, interactive, and disposable. You describe what you want to see in plain English, and Lopus builds the dashboard in seconds. You can drill into any chart, ask follow-up questions, change filters, and explore your data interactively. Build ten dashboards. Build a hundred. Throw them away and build new ones the next day. The cost of creating a dashboard drops to near zero, which means you always have the exact view you need right now — not the one someone built for you last quarter.
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Does Lopus work for early-stage startups?
Yes. Lopus is designed for companies from seed stage through Series C and beyond. Early-stage startups are often the best fit because they have the most acute version of the problem: data scattered across 6-7 tools, no data team, and a founder or engineer spending Sunday afternoons compiling board decks manually. Lopus gives seed-stage founders immediate access to MRR tracking, funnel analysis, cohort retention, and investor-ready metrics without hiring a data person. For Series A companies preparing for fundraising or board reporting, Lopus produces the NRR, CAC by channel, and cohort analysis that investors expect — in minutes, not days.
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Does Lopus work for early-stage startups?
Yes. Lopus is designed for companies from seed stage through Series C and beyond. Early-stage startups are often the best fit because they have the most acute version of the problem: data scattered across 6-7 tools, no data team, and a founder or engineer spending Sunday afternoons compiling board decks manually. Lopus gives seed-stage founders immediate access to MRR tracking, funnel analysis, cohort retention, and investor-ready metrics without hiring a data person. For Series A companies preparing for fundraising or board reporting, Lopus produces the NRR, CAC by channel, and cohort analysis that investors expect — in minutes, not days.
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Does Lopus work for early-stage startups?
Yes. Lopus is designed for companies from seed stage through Series C and beyond. Early-stage startups are often the best fit because they have the most acute version of the problem: data scattered across 6-7 tools, no data team, and a founder or engineer spending Sunday afternoons compiling board decks manually. Lopus gives seed-stage founders immediate access to MRR tracking, funnel analysis, cohort retention, and investor-ready metrics without hiring a data person. For Series A companies preparing for fundraising or board reporting, Lopus produces the NRR, CAC by channel, and cohort analysis that investors expect — in minutes, not days.
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What happens if my underlying data is messy?
Lopus is designed to work with messy data. Most companies have 3–5 years of accumulated schema debt, deprecated fields, inconsistent naming, and incomplete records across their tools. Lopus does not assume your data is already clean. During setup, your Forward-Deployed Engineer audits your data sources, identifies field conflicts and deprecated fields, resolves entity identities across systems, and builds a curated semantic layer that gives the AI correct context. The semantic layer acts as a filter — it tells the AI which fields to use and which to ignore, preventing the "wrong field" errors that plague other AI analytics tools when they connect to unclean data.
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What happens if my underlying data is messy?
Lopus is designed to work with messy data. Most companies have 3–5 years of accumulated schema debt, deprecated fields, inconsistent naming, and incomplete records across their tools. Lopus does not assume your data is already clean. During setup, your Forward-Deployed Engineer audits your data sources, identifies field conflicts and deprecated fields, resolves entity identities across systems, and builds a curated semantic layer that gives the AI correct context. The semantic layer acts as a filter — it tells the AI which fields to use and which to ignore, preventing the "wrong field" errors that plague other AI analytics tools when they connect to unclean data.
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Can Lopus help with board reporting and investor metrics?
Yes. Lopus can generate the exact metrics investors and board members expect — MRR/ARR, net revenue retention, churn rate, CAC by channel, LTV by cohort, pipeline coverage, and payback period — from your unified data, in seconds. Board deck preparation that currently takes a full day of pulling CSVs from Stripe, HubSpot, and spreadsheets becomes a single question in Lopus. Metrics are always current because they pull from live data, not last month's export.
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What is the difference between Lopus and tools like Glean?
Glean is an AI assistant that surfaces and organizes information across your existing tools — summarizing Slack threads, finding documents, triaging notifications - it's a management and organization tool. Lopus is an analytics and intelligence platform. It doesn't surface what already exists — it computes answers that didn't previously exist by querying, correlating, and analyzing data across multiple systems. The difference is surfacing vs. analyzing. Glean tells you where a document is. Lopus tells you why churn dropped, which rep is underperforming, and which customer segment is growing — answers that live across multiple systems and need to be computed, not just found.
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Does Lopus support alerts and notifications?
Yes. Canary Alerts monitor any metric you define and send notifications to Slack or email when something changes. You set the thresholds — pipeline drops below a target, conversion rate shifts by more than 5%, churn rate spikes, a specific account goes inactive — and Canary watches continuously. This means you don't need to check dashboards manually every morning. Canary brings the important changes to you, proactively, so you can focus on decisions instead of monitoring.
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Does Lopus support alerts and notifications?
Yes. Canary Alerts monitor any metric you define and send notifications to Slack or email when something changes. You set the thresholds — pipeline drops below a target, conversion rate shifts by more than 5%, churn rate spikes, a specific account goes inactive — and Canary watches continuously. This means you don't need to check dashboards manually every morning. Canary brings the important changes to you, proactively, so you can focus on decisions instead of monitoring.
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Can multiple teams use Lopus at the same company?
Yes. Lopus supports multiple teams with permissioned access. Sales, marketing, product, finance, and leadership can all query the same unified data — but access controls determine who can see which datasets, build dashboards, share externally, or modify business definitions. The same underlying data powers different views for different roles. A CRO sees pipeline and revenue metrics. A product manager sees feature adoption and activation rates. A founder sees the full picture across all departments. One source of truth, many perspectives.
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Can multiple teams use Lopus at the same company?
Yes. Lopus supports multiple teams with permissioned access. Sales, marketing, product, finance, and leadership can all query the same unified data — but access controls determine who can see which datasets, build dashboards, share externally, or modify business definitions. The same underlying data powers different views for different roles. A CRO sees pipeline and revenue metrics. A product manager sees feature adoption and activation rates. A founder sees the full picture across all departments. One source of truth, many perspectives.
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How does Lopus handle cross-system data like CAC by channel or cohort retention?
Cross-system analysis is where Lopus delivers the most value. Metrics like CAC by channel require CRM data joined with billing data. Cohort retention requires product analytics joined with revenue data. Customer health scores require data from product, support, and billing systems combined. Most companies can't produce these metrics because their data lives in separate tools with no shared identity. Lopus solves this through its unified data warehouse, semantic layer, and identity graph — every customer, account, and interaction is mapped across systems during setup. You ask "What's my CAC by marketing channel?" and Lopus joins HubSpot attribution data with Stripe revenue data automatically.
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What does "no maintenance" mean?
It means your team does not maintain data pipelines, warehouse infrastructure, schema mappings, or dashboard configurations. Lopus manages all of this as part of the platform. Data syncs are set up for you and run automatically. Schema changes in your source tools are detected and handled. Your semantic layer stays current as your business evolves. If you add a new data source or change a business definition, your Forward-Deployed Engineer updates the configuration. You never open a terminal, write a migration, or debug a broken pipeline.
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What does "no maintenance" mean?
It means your team does not maintain data pipelines, warehouse infrastructure, schema mappings, or dashboard configurations. Lopus manages all of this as part of the platform. Data syncs are set up for you and run automatically. Schema changes in your source tools are detected and handled. Your semantic layer stays current as your business evolves. If you add a new data source or change a business definition, your Forward-Deployed Engineer updates the configuration. You never open a terminal, write a migration, or debug a broken pipeline.
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