The platform behind every solution.
A fully managed, cloud-native environment that absorbs the infrastructure, the security, and the AI operations. Your data stays isolated and stays yours. What we build on it is yours to keep, and it is production-grade from day zero.
The hard parts of enterprise AI, handled.
Most teams that try to put AI into production get stuck in the same place: the infrastructure, the security, the model operations, the integrations. Our platform takes all of it, so your team does not have to build or run any of it.
01
Model operations, failover, and vendor API updates
02
Security patching and infrastructure maintenance
03
The cost and risk of keeping all of it running
Security your diligence team can check.
Security is built into the platform, not added at the end. We have the full security picture written for your diligence team.
Certification
SOC 2 aligned and maturing toward certification, governed by 35+ security policies.
Encryption
At rest via managed database encryption; in transit via TLS 1.2 or higher.
Access control
Role-based access, multi-factor authentication, and enterprise SSO.
Built for you, on a platform we run.
Here is the line that matters: you own the AI motion, we own the infrastructure.
You own
The workflows, the domain intelligence, the data models, and the compounding IP the solution builds for your business.
We run
The compute, the Kubernetes clusters, the model operations, the security patching, and the vendor updates.
One system, from intake to decision.
Work comes in however it arrives. The platform routes it to the right AI model, processes it with agents that scale to the load, pushes the result into the systems you run, and sends only the exceptions to your people. Every step is logged, and what it learns is yours.
Ingest
Email-native intake, any format, standard protocols.
Ingest
Route
The right AI model for each task, with automatic failover.
Route
Process
Autonomous agents that scale with demand.
Process
Integrate
Clean data into Salesforce, NetSuite, or any other systems you run.
Integrate
Review
Exceptions to your people; the AI learns from every correction.
Review
Audit
Every action logged, every change versioned.
Audit
Never betting on a single model.
The platform sends each workflow to the best model for the job, OpenAI, Anthropic, Google, and switches automatically if a provider goes down or a better model ships. Token costs are tracked per call, so you always know what the intelligence is costing you.
Multi-model routing
The right model per task, not one vendor’s roadmap.
Automatic failover
If a provider goes down, the work keeps moving.
Cost transparency
Token spend tracked on every call.
The platform’s own copilot
Trained on the platform itself, SolutionAI helps design data strategies, map workflows, connect APIs, and write the custom code, so solutions get built faster.
Built to run in production, not in a demo.
The platform runs on Microsoft Azure-managed services, keeps every client fully isolated, and ships changes without taking anything down.
01
Azure-native infrastructure
Managed cloud services, built to scale. [Full infrastructure detail lives in the docs; public-naming scope pending CTX.]
02
Isolated by architecture
Each client is its own security boundary, with separate data, compute, and event streams.
03
Zero-downtime deploys
Updates and rollbacks happen by rolling replacement, with no outage.
04
Test-gated promotion
Every change moves from development to staging to production through automated tests and peer review.
05
Deep observability
Real-time dashboards on health, latency and queue depth, with every configuration change logged immutably.
06
Read-only staging
Through build and testing your AI reads from your systems without writing to them. Nothing reaches a system of record until you sign off. [Pending CTX: confirm how this works in practice
99%
Uptime / SLA
4k
Volume processed
15ms
Inference latency
Into the systems you already run.
Your AI shows up inside your existing tools, grounded in your real data.
Define once, no custom code
Invoices are picked up where they already arrive, in whatever format they arrive in.
Grounded, cited answers
Work orders are created in the system your operation already runs on, linked to the right vendor and asset.
Connect anything
Your team reviews only what needs judgment, and the AI learns from every correction.
Not a roadmap, a production system.
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