For analysts and business teams tired of the data-team queue
Stop waiting 2–3 days for a SQL query someone else could have written in ten minutes.
Hawk AI lets your team ask questions in plain English and get governed, trustworthy SQL answers — no ticket, no SQL knowledge required, and no bypass of the access control your DBAs already rely on.
Private by design No third-party training Add-on to your DBHawk license 
What is text-to-SQL AI?
An AI SQL query tool turns plain-English questions into working SQL, without asking analysts to learn database schemas or SQL syntax. Hawk AI is DataSparc’s natural language to SQL layer: a text-to-SQL AI that works as an AI database assistant across MySQL, PostgreSQL, SQL Server, Oracle, Snowflake and every other database connected to DBHawk. Every Hawk AI session is exposed through the built-in Hawk AI MCP Server, so enterprise AI data governance rules apply whether a person or an autonomous agent is asking the question — the same object-level access control, the same audit trail.
The problem
Most business questions aren't complicated — the wait is
Finding the right tables, writing a correct join, and waiting in a backlog for a data team's review adds days to a question that should take minutes.
2–3 day round trip
A minor filter tweak means resubmitting the ticket and waiting in the queue again.
DBA and data-team time spent
Every ad hoc question also costs the data team's time in review and handling — time they don't get back.
Shadow AI risk
Teams route around slow processes with ungoverned copilots that bypass access control entirely.
What this adds up to
≈1.3 hours saved per governed question
hours saved / month (25 analysts, 8 questions each)
hours saved / year
FTEs of analyst time freed annually
How Hawk AI solves it
Natural language in, governed SQL out
Governed by the same rules
Object-level access control applies to AI-assisted sessions exactly as it does to manual queries.
Private by design
Runs on a self-hosted Ollama model or your own Azure OpenAI instance — never a public, multi-tenant AI service.
No new credentials
Users sign in with existing company SSO — access resolves from the same directory groups.
Governed agent connectivity
The built-in Hawk AI MCP Server lets external AI agents reach your data through the same access control and audit trail.
Key features
Natural language to SQL for every connected database
Private by design (self-hosted Ollama or private Azure OpenAI)
Object-level access control on every AI SQL session
No new credentials — resolves from existing SSO groups
Granular AI data-sharing per database, schema, table or column
Audit logging exportable to Splunk, Elastic, Azure Monitor
Built-in Hawk AI MCP Server for external AI agents
Text-to-SQL AI in any language
AI-generated charts from any SQL query result
Strengths
Why Hawk AI is different from a bolted-on copilot
Bring your own model
Run the specific model you trust — open-source or commercial — instead of one vendor's hosted model.
Never public, multi-tenant
Inference runs on infrastructure you control, and is never used for third-party model training.
Zero Trust by design
An AI agent gets exactly the access a human in its role would get — no more.
Use cases
Where Hawk AI fits into your team's workflow
Self-service analytics
Business users ask questions in plain English and get governed results, plus AI-generated charts.
Faster SQL development
Developers get query drafts, optimization tips and plain-language explanations of complex SQL.
Schema documentation
Auto-generate table, view and column descriptions to speed up onboarding.
Secure agentic workflows
Connect external AI agents to production data via the MCP Server — no raw credentials, no bypassed governance.
See Hawk AI answer a real question from your own schema
A guided pilot runs on a scoped schema with your own AI infrastructure.
Why teams trust Hawk AI
Governed the moment it's turned on
Same SSO, same object-level permissions
Every request audit-logged, exportable to Splunk/Elastic
Never used for third-party model training
From the founder
“Every team is under pressure to ‘do something with AI’ this year. The mistake we see most often is bolting a copilot onto production data with none of the access control that took years to build. Hawk AI was our answer to doing this the right way from day one.”
– Manish Shah, Founder & CEO, Datasparc
FAQ
Common questions from data and security teams
Does Hawk AI send our data to a public AI service?
No. Hawk AI runs on a self-hosted Ollama model or your own private Azure OpenAI instance — never a public, multi-tenant AI API.
Can Hawk AI see data an analyst isn't allowed to see?
No. Object-level access control applies to AI-assisted sessions exactly as it does to manual queries.
Can external AI agents connect through Hawk AI?
Yes, through the built-in Hawk AI MCP Server, which enforces the same access control and audit trail as any other session.
Is our data used to train any model?
Never. Inference runs on infrastructure you control and is never used for third-party model training.
Which databases does this AI SQL query tool support?
Every database connected to DBHawk, including MySQL, PostgreSQL, SQL Server, Oracle, Snowflake, MongoDB and 20+ more.
Explore the platform
Hawk AI runs on top of your existing DBHawk access model
DBHawk →
The Zero Trust data access platform Hawk AI’s governance is built on top of.
Audit & Compliance Dashboard →
Every Hawk AI prompt and query is logged in the same cross-database audit trail.
Latest on governed AI and natural-language analytics
Ready to turn ad hoc questions into a self-service, governed conversation?
Start free, or scope a pilot for your own AI infrastructure.