Design the workflow
Map the customer path, service steps, queues, approvals, and completion points before the first run touches real work.
Build AI systems that stay understandable after launch.
EngineGrids gives developers one place to build, launch, and inspect AI systems through a SQL-native control plane. Replace fragile provider glue with platform state that keeps production work readable.
Day 1 developers
Give builders a real design surface for the first system they need to ship.
EngineGrids lets developers model workflows, runtime grids, agents, evidence logs, approvals, and handoffs in the same workspace where the system will be built, inspected, and prepared for production.
Inspect every element
Keep names, trigger modes, durability rules, retry policies, and evidence requirements visible while the design is still changing.
Build before deploy
Use build checks and assistant feedback to catch missing mappings and deployment blockers while the system is still safe to change.
Developer story
The deterministic runtime for AI systems that stay production-credible.
EngineGrids gives developers more speed at the front and more operational clarity at the back. We replace brittle integration glue with a governed operating surface built for the long horizon.
Manage installs, runtime behavior, and provider actions through a deterministic data interface.
Replace fragmented provider libraries with governed app surfaces and durable platform state.
Every action is an auditable row.
Inspect, replay, and explain production behavior with zero runtime fog.
Let the platform resolve services, apps, and bindings in dependency order.
Speed at the front should not become unmanaged runtime behavior after launch.
Developer proof
Build quickly without handing the business an unexplainable runtime later.
Install capability
Subscribing to a service through grid.services auto-installs the app surfaces and bindings the grid needs.
SQL
insert into grid.services (name, plan)
values ('stripe', 'production');Perform actions
Instead of calling brittle SDKs, insert intent into governed tables. Sidecar handles the provider work.
SQL
insert into stripe.invoices (customer_id, amount, currency)
values ('cust_123', 4200, 'usd');Audit and replay
Every action produces a durable audit row. Inspect intent, execution, and provider response in one place.
SQL
select * from platform.audits
where object_id = 'inv_123'
order by created_at desc;Manage installs, runtime behavior, and provider actions through a deterministic data interface.
Build on tables where intent and outcome are always auditable.
Replace fragmented provider libraries with governed app surfaces.
Keep agent logic clean while the platform carries provider complexity.
Let the platform resolve services, apps, and bindings in dependency order.
Install capability through grid.services instead of rebuilding connector paths.
Every action is an auditable row.
Inspect, replay, and explain production behavior with clear runtime history.
Day-one speed should not create day-two fog.
EngineGrids helps developers move quickly while keeping runtime behavior visible to the operators and business owners who inherit the system.
Subscribe through grid.services
A service subscription auto-installs the app surfaces and bindings the grid needs.
Insert intent into governed tables
Instead of calling brittle SDKs, write intent into tables and let sidecar handle provider work.
Inspect intent, execution, and provider response
Every action produces a durable audit row that survives production scale.
Keep the technical story readable to the business
The system should explain what it did, why it did it, and what changed after it ran.
Move quickly without handing the business a black box later.
Use the platform model, trust threshold, and documentation to build serious AI systems without losing runtime clarity.
See the platform model
Go deeper into the control plane that turns installs, runtime, real-system work, and audits into one operating model.
See the platformSee the trust threshold
Understand why this runtime matters once AI touches customers, money, records, and real workflows.
See trustRead the technical guides
Use the documentation center when you need the product surface and implementation detail.
Read docsMove quickly now without leaving day-two operators guessing later.
Build the first system with clear runtime controls, readable action history, and enough structure for operators to trust it when real work begins.