Prompts reveal your sensitive data. We keep it private.
Prompts reveal your sensitive data. We keep it private.
Prompts reveal your sensitive data. We keep it private.
Chata.ai’s AI agents monitor your metrics, summarize what changed and recommend your next move. Built-in data obfuscation hides sensitive values before any question reaches the LLM.
Chata.ai’s AI agents monitor your metrics, summarize what changed and recommend your next move. Built-in data obfuscation hides sensitive values before any question reaches the LLM.
ISO 27001 Certified
SOC 2 Type II Attested
1 Ask
2 Mask
3 SQL
4 Answer
Start a new query…
WHAT A TYPICAL LLM RECEIVES
Which of Northgate Capital’s portfolios had trades settled through Alder Street Securities after Ryan Holloway left the desk?
Client and counterparty names exposed
WHAT THE LLM RECEIVES WITH CHATA.AI
Which of
Northgate Capital
’s portfolios had trades settled
through
Alder Street Securities
after
Ryan Holloway
left the desk?
Sensitive values masked before the LLM
SQL CHATA.AI GENERATES
Inside your environment
query.sql
SELECT p.portfolio_name, COUNT(t.trade_id) AS trades_settled, SUM(t.notional_value) AS total_notional_usd, MIN(t.settlement_date) AS first_settlement, MAX(t.settlement_date) AS last_settlement
FROM trades t
JOIN portfolios p ON t.portfolio_id = p.portfolio_id
JOIN firms f ON p.firm_id = f.firm_id
JOIN brokers b ON t.settlement_broker_id = b.broker_id
WHERE f.firm_name =
AND b.broker_name =
AND t.settlement_date > ( SELECT e.desk_end_date FROM employees e WHERE e.full_name = )
GROUP BY p.portfolio_name
ORDER BY total_notional_usd DESC;
This SQL runs inside your environment. The LLM never sees it or your data.
Which of Northgate Capital’s portfolios had trades settled through Alder Street Securities after Ryan Holloway left the desk?
Ryan Holloway’s desk end date: June 30, 2026.
Portfolio
Trades Settled
Total Notional (USD)
First Settlement
Last Settlement
Northgate Global Equity
142
$48,350,000
Jul 2, 2026
Nov 6, 2026
Northgate Fixed Income Plus
87
$31,920,000
Jul 8, 2026
Nov 4, 2026
Northgate Emerging Markets
54
$12,615,000
Jul 15, 2026
Oct 29, 2026
Northgate Balanced Growth
23
$6,480,000
Aug 3, 2026
Oct 21, 2026
Interpreted as: Portfolios at Northgate Capital with trades settled through Alder Street Securities after Ryan Holloway’s desk end date, by total notional.
Privacy-enabled self-service analytics
1 Ask
2 Mask
3 SQL
4 Answer
Start a new query…
WHAT A TYPICAL LLM RECEIVES
Which of Northgate Capital’s portfolios had trades settled through Alder Street Securities after Ryan Holloway left the desk?
Client and counterparty names exposed
WHAT THE LLM RECEIVES WITH CHATA.AI
Which of
Northgate Capital
’s portfolios had trades settled
through
Alder Street Securities
after
Ryan Holloway
left the desk?
Sensitive values masked before the LLM
SQL CHATA.AI GENERATES
Inside your environment
query.sql
SELECT p.portfolio_name, COUNT(t.trade_id) AS trades_settled, SUM(t.notional_value) AS total_notional_usd, MIN(t.settlement_date) AS first_settlement, MAX(t.settlement_date) AS last_settlement
FROM trades t
JOIN portfolios p ON t.portfolio_id = p.portfolio_id
JOIN firms f ON p.firm_id = f.firm_id
JOIN brokers b ON t.settlement_broker_id = b.broker_id
WHERE f.firm_name =
AND b.broker_name =
AND t.settlement_date > ( SELECT e.desk_end_date FROM employees e WHERE e.full_name = )
GROUP BY p.portfolio_name
ORDER BY total_notional_usd DESC;
This SQL runs inside your environment. The LLM never sees it or your data.
Which of Northgate Capital’s portfolios had trades settled through Alder Street Securities after Ryan Holloway left the desk?
Ryan Holloway’s desk end date: June 30, 2026.
Portfolio
Trades Settled
Total Notional (USD)
First Settlement
Last Settlement
Northgate Global Equity
142
$48,350,000
Jul 2, 2026
Nov 6, 2026
Northgate Fixed Income Plus
87
$31,920,000
Jul 8, 2026
Nov 4, 2026
Northgate Emerging Markets
54
$12,615,000
Jul 15, 2026
Oct 29, 2026
Northgate Balanced Growth
23
$6,480,000
Aug 3, 2026
Oct 21, 2026
Interpreted as: Portfolios at Northgate Capital with trades settled through Alder Street Securities after Ryan Holloway’s desk end date, by total notional.
Privacy-enabled self-service analytics
Why Teams Trust Chata.ai for High-Risk Decisions
Automating data work shouldn’t mean giving up privacy. Chata.ai is built to give you both.
Automating data work shouldn’t mean giving up privacy. Chata.ai is built to give you both.
Keep Data Private
Audit Every Result
Cut Compute Costs
Track Across Sources
Sensitive business context may leak through the prompts users send to LLMs. Other companies promise to delete prompt data after it is sent, but "deletion" does not mean zero exposure.
With Chata.ai, your proprietary details — client information, transactions, anything identifying — are masked before any information reaches an LLM.
Keep Data Private
Audit Every Result
Cut Compute Costs
Track Across Sources
Sensitive business context may leak through the prompts users send to LLMs. Other companies promise to delete prompt data after it is sent, but "deletion" does not mean zero exposure.
With Chata.ai, your proprietary details — client information, transactions, anything identifying — are masked before any information reaches an LLM.
Keep Data Private
Audit Every Result
Cut Compute Costs
Track Across Sources
Sensitive business context may leak through the prompts users send to LLMs. Other companies promise to delete prompt data after it is sent, but "deletion" does not mean zero exposure.
With Chata.ai, your proprietary details — client information, transactions, anything identifying — are masked before any information reaches an LLM.
Your Data, Fully Protected
ISO 27001 Certified
SOC 2 Type II Attested
Reduce the Time from Signal to Insight to Action
Reduce the Time from Signal to Insight to Action
Proven Across Industries
From prediction markets to wealth management, purpose-built automation and analytics products run on the same privacy-enabled engine, putting trusted self-service insights right where decisions get made.
Turn prediction markets into practical tools for managing financial and operational risk.
Track transactions, fees and rewards on the Canton Network, sensitive data stays private.
Give advisors instant insights on any client, account or portfolio.
Analyze any player or team, get real‑time alerts across NFL, NBA, NHL, and MLB.
Real Results, Real Impact
Real Results, Real Impact
3×
faster financial insights
24/7
real-time analytics coverage and anomaly detection
0%
hallucinations or probabilities
What Our Satisfied Customers Say
Hear from satisfied customers who've transformed their businesses. Real experiences, real results – see what's possible with us.
Employing Chata’s Decision Intelligence within Dialect allows users (DIY investors or financial professionals alike) to access and analyze stock market data quickly and efficiently.
Anthony Trzeciak
Dialect
Chata’s integration with Azure has resulted in a solution that brings innovation enabling strategic actions to be taken right away, an advantage that benefits businesses of all sizes.
Suzanne Gagliese
Microsoft Canada
At IntellectEU, we see Sync Insights (built with Chata.ai) delivering exactly what CatalyX Suite users and the wider Canton Network need: an easy, reliable way to track transaction activity and network charges like fees, rewards, and transfers.
Anastasiia Vitmer
IntellectEU
Providing this capability sets Dialect apart because, now anyone can make data-driven decisions by simply asking questions, filtering data, and setting alerts in seconds.
Anthony Trzeciak
Dialect
Microsoft Azure customers can use AutoQL to streamline access to data for everyone from executives to analysts and front-line workers.
Suzanne Gagliese
Microsoft Canada
Employing Chata’s Decision Intelligence within Dialect allows users (DIY investors or financial professionals alike) to access and analyze stock market data quickly and efficiently.
Anthony Trzeciak
Dialect
Chata’s integration with Azure has resulted in a solution that brings innovation enabling strategic actions to be taken right away, an advantage that benefits businesses of all sizes.
Suzanne Gagliese
Microsoft Canada
Providing this capability sets Dialect apart because, now anyone can make data-driven decisions by simply asking questions, filtering data, and setting alerts in seconds.
Anthony Trzeciak
Dialect
Microsoft Azure customers can use AutoQL to streamline access to data for everyone from executives to analysts and front-line workers.
Suzanne Gagliese
Microsoft Canada
Official Microsoft & Google Cloud Partner
Marketplace Transactable
Frequently Asked Questions
How is my data protected when using AI?
Chata.ai is built so your data stays under your control at every step.
Runs in your environment: Chata.ai deploys in your cloud or on-premise infrastructure and work with your data without moving or copying it.
Sensitive and proprietary data is masked: Queries are obfuscated before they ever reach an LLM, so no proprietary data gets disclosed. You decide which fields are protected.
Your governance applies: Chata.ai follows your existing permissions, including role-based access and row- and column-level security.
Every request is auditable: Each action is logged and traceable from input to result, and only safe, read-only queries are allowed.
Independently certified: Chata.ai is ISO 27001 certified and SOC 2 Type II attested, and your data is never used to train AI models.
How is my data protected when using AI?
Chata.ai is built so your data stays under your control at every step.
Runs in your environment: Chata.ai deploys in your cloud or on-premise infrastructure and work with your data without moving or copying it.
Sensitive and proprietary data is masked: Queries are obfuscated before they ever reach an LLM, so no proprietary data gets disclosed. You decide which fields are protected.
Your governance applies: Chata.ai follows your existing permissions, including role-based access and row- and column-level security.
Every request is auditable: Each action is logged and traceable from input to result, and only safe, read-only queries are allowed.
Independently certified: Chata.ai is ISO 27001 certified and SOC 2 Type II attested, and your data is never used to train AI models.
How is my data protected when using AI?
Chata.ai is built so your data stays under your control at every step.
Runs in your environment: Chata.ai deploys in your cloud or on-premise infrastructure and work with your data without moving or copying it.
Sensitive and proprietary data is masked: Queries are obfuscated before they ever reach an LLM, so no proprietary data gets disclosed. You decide which fields are protected.
Your governance applies: Chata.ai follows your existing permissions, including role-based access and row- and column-level security.
Every request is auditable: Each action is logged and traceable from input to result, and only safe, read-only queries are allowed.
Independently certified: Chata.ai is ISO 27001 certified and SOC 2 Type II attested, and your data is never used to train AI models.
What is the technology behind Chata.ai?
Chata.ai offers two approaches, so you can match the technology to the workload:
[Privacy-Enabled Pipeline]: our main platform for flexible self-service analytics, that provides powerful agentic and automation capabilities. AI interprets questions using your business logic, sensitive data is masked before reaching LLMs, and every step is validated and auditable. It handles complex questions and tasks, and can join contexts across related datasets.
[Core Deterministic Model]: built for regulated reporting and compliance workflows where the same question must always return the same answer. It runs fully on CPU and needs no generative AI.
Our team can help you decide which fits each use case.
What is the technology behind Chata.ai?
Chata.ai offers two approaches, so you can match the technology to the workload:
[Privacy-Enabled Pipeline]: our main platform for flexible self-service analytics, that provides powerful agentic and automation capabilities. AI interprets questions using your business logic, sensitive data is masked before reaching LLMs, and every step is validated and auditable. It handles complex questions and tasks, and can join contexts across related datasets.
[Core Deterministic Model]: built for regulated reporting and compliance workflows where the same question must always return the same answer. It runs fully on CPU and needs no generative AI.
Our team can help you decide which fits each use case.
What is the technology behind Chata.ai?
Chata.ai offers two approaches, so you can match the technology to the workload:
[Privacy-Enabled Pipeline]: our main platform for flexible self-service analytics, that provides powerful agentic and automation capabilities. AI interprets questions using your business logic, sensitive data is masked before reaching LLMs, and every step is validated and auditable. It handles complex questions and tasks, and can join contexts across related datasets.
[Core Deterministic Model]: built for regulated reporting and compliance workflows where the same question must always return the same answer. It runs fully on CPU and needs no generative AI.
Our team can help you decide which fits each use case.
Which AI models do you use? Can I choose?
Chata.ai works with a range of LLMs, and you can choose the one that fits your requirements. Our [privacy-enabled pipeline] uses CPU wherever possible and lightweight models where AI is needed, keeping costs and energy use low.
Which AI models do you use? Can I choose?
Chata.ai works with a range of LLMs, and you can choose the one that fits your requirements. Our [privacy-enabled pipeline] uses CPU wherever possible and lightweight models where AI is needed, keeping costs and energy use low.
Which AI models do you use? Can I choose?
Chata.ai works with a range of LLMs, and you can choose the one that fits your requirements. Our [privacy-enabled pipeline] uses CPU wherever possible and lightweight models where AI is needed, keeping costs and energy use low.
How can we introduce self-service BI while maintaining governance?
Self-service doesn’t mean giving up oversight. With the right permissions, data models, and audit trails in place, business users can explore data safely while IT and data teams maintain governance, accuracy, and security. Chata.ai helps to follow governance policies behind the scenes so teams can move fast without risk or losing data control.
How can we introduce self-service BI while maintaining governance?
Self-service doesn’t mean giving up oversight. With the right permissions, data models, and audit trails in place, business users can explore data safely while IT and data teams maintain governance, accuracy, and security. Chata.ai helps to follow governance policies behind the scenes so teams can move fast without risk or losing data control.
How can we introduce self-service BI while maintaining governance?
Self-service doesn’t mean giving up oversight. With the right permissions, data models, and audit trails in place, business users can explore data safely while IT and data teams maintain governance, accuracy, and security. Chata.ai helps to follow governance policies behind the scenes so teams can move fast without risk or losing data control.
How does the platform integrate with existing data warehouses and tools?
Chata.ai is designed to fit into your current data environment. It integrates with popular data warehouses, BI tools, and other tools, so you don’t have to rebuild your ecosystem. Once you connect, you can start asking questions in plain language, instantly accessing the same trusted data your teams already use.
How does the platform integrate with existing data warehouses and tools?
Chata.ai is designed to fit into your current data environment. It integrates with popular data warehouses, BI tools, and other tools, so you don’t have to rebuild your ecosystem. Once you connect, you can start asking questions in plain language, instantly accessing the same trusted data your teams already use.
How does the platform integrate with existing data warehouses and tools?
Chata.ai is designed to fit into your current data environment. It integrates with popular data warehouses, BI tools, and other tools, so you don’t have to rebuild your ecosystem. Once you connect, you can start asking questions in plain language, instantly accessing the same trusted data your teams already use.
How does proactive analytics reduce manual reporting workload?
Proactive analytics automatically detects trends and changes in your data and shares them with the right people. This means teams spend less time building or refreshing reports and more time acting on insights. It turns what used to be a manual process into an automated one.
How does proactive analytics reduce manual reporting workload?
Proactive analytics automatically detects trends and changes in your data and shares them with the right people. This means teams spend less time building or refreshing reports and more time acting on insights. It turns what used to be a manual process into an automated one.
How does proactive analytics reduce manual reporting workload?
Proactive analytics automatically detects trends and changes in your data and shares them with the right people. This means teams spend less time building or refreshing reports and more time acting on insights. It turns what used to be a manual process into an automated one.
What makes Chata.ai different from traditional BI or dashboard tools
Traditional BI tools rely on pre-built dashboards and manual reports, which often lag behind fast-moving business needs. Chata.ai goes further by automating insights delivery across fragmented data sources, giving business users real-time, trustworthy data they can act on proactively.
This means your teams don’t just view historical performance; they can detect issues and uncover opportunities before they impact results. Combined with natural language queries, Chata.ai reduces manual reporting, accelerates decision-making, and scales across diverse environments.
What makes Chata.ai different from traditional BI or dashboard tools
Traditional BI tools rely on pre-built dashboards and manual reports, which often lag behind fast-moving business needs. Chata.ai goes further by automating insights delivery across fragmented data sources, giving business users real-time, trustworthy data they can act on proactively.
This means your teams don’t just view historical performance; they can detect issues and uncover opportunities before they impact results. Combined with natural language queries, Chata.ai reduces manual reporting, accelerates decision-making, and scales across diverse environments.
What makes Chata.ai different from traditional BI or dashboard tools
Traditional BI tools rely on pre-built dashboards and manual reports, which often lag behind fast-moving business needs. Chata.ai goes further by automating insights delivery across fragmented data sources, giving business users real-time, trustworthy data they can act on proactively.
This means your teams don’t just view historical performance; they can detect issues and uncover opportunities before they impact results. Combined with natural language queries, Chata.ai reduces manual reporting, accelerates decision-making, and scales across diverse environments.
Proactive Analytics, Private by Design
See What Happens
When Analytics
Go Proactive
From detection to decision — see the difference alerts, automation and agentic AI can make, with sensitive data protected along the way.