OGAC
Summary
Every enterprise AI rollout eventually hits the same wall: a compliance team that can't audit what the model said last Tuesday, and a dev team re-implementing the same guardrails in every new app. Off Grid AI Console exists to collapse that problem into a single governed control plane.
The Console gives banks, insurers, and other regulated enterprises one place to connect data sources, route traffic through observed model gateways, build apps in plain language without code, and produce signed, cited audit trails — all governed by rules set once and inherited everywhere. Prompt-injection screening, PII filtering, and policy checks run in the pipe before a call leaves the system. Live scoring watches for drift against a golden set and traces every result to its source. A run can pause for human sign-off, then continue on its own. The self-hosted, AGPL-3.0 path means your data and models stay on your servers — but operating that infrastructure is on your team, not the vendor.
Bottom line: Pick this when your compliance team needs a signed audit trail before any AI output reaches a customer — plan for real infrastructure investment if you self-host, and expect the plain-language builder to hit its ceiling the moment a workflow needs logic your business team cannot describe in a sentence.
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Pros
Sign in to edit- Rules set once and inherited by every app and agent built on the platform, so compliance teams stop chasing developers to re-implement guardrails each time a new use case ships.
- Prompt-injection, PII, and policy screening run inside the pipeline before a call exits the system, which means a blocked request never reaches an external model or a downstream user.
- Live drift scoring and source tracing on every run, so when a regulator asks what the model said and why, the answer is already signed and cited rather than reconstructed from scattered logs.
- AGPL-3.0 open-source with full self-host support, so your model traffic and data stay on your servers and swapping a gateway or model provider is a config change rather than a renegotiated contract.
- Human oversight pauses built into agent runs, so a workflow that touches a sensitive decision stops for sign-off before continuing — without requiring a custom integration to wire that step in.
Cons
Sign in to edit- The plain-language app builder targets business teams describing clear, bounded use cases — workflows that require conditional branching across multiple decision points force developer involvement, at which point teams are maintaining both the no-code layer and custom logic sitting outside it.
- Self-hosting under AGPL-3.0 puts infrastructure operation, scaling, and security patching on your team; organizations without dedicated platform engineering capacity report that the operational overhead shifts cost from licensing to headcount, and some move to a managed alternative when internal bandwidth runs out.
- The vendor's public pricing page does not list usage tiers or per-seat costs, so teams cannot estimate total cost of ownership without booking a demo — a blocking issue for procurement processes that require a written quote before evaluation can proceed.
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About
- Platforms
- Cloud, on-prem, self-hosted
- API Available
- Yes
- Self-Hosted
- Yes
- Last Updated
- 2026-07-14T06:18:25.827Z
Best For
Who it's for
- Banks and insurers needing regulated AI deployment
- Enterprises requiring end-to-end AI governance
- Teams wanting no-code agent and app building
- Organizations seeking open-source self-hosted AI control planes
What it does well
- Building governed AI apps in plain language for business teams
- Routing traffic through observed model gateways on-prem or cloud
- Enforcing enterprise-wide compliance and audit trails
- Monitoring live AI runs for drift and source tracing
- Deploying agentic workflows with human oversight pauses
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Frequently Asked Questions
- Is OGAC free?
- OGAC has a permanent free tier alongside paid upgrades. You can keep using a baseline version indefinitely without paying.
- Is OGAC open source?
- No — OGAC is a closed-source tool. Source code is not publicly available.
- Does OGAC have an API?
- Yes. OGAC exposes a developer API. See the official documentation at https://onprem-console.getoffgridai.co for details.
- Can I self-host OGAC?
- Yes. OGAC supports self-hosting on your own infrastructure.
- What platforms does OGAC support?
- OGAC is available on: Cloud, on-prem, self-hosted.
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Curated lists that include this category
Off Grid AI Console is a self-hosted or cloud-deployed AI governance platform built for enterprises where every model call must be logged, auditable, and policy-compliant before it reaches production. The core workflow runs in five stages the vendor describes as a single path: data from existing systems flows into observed model gateways, through governed pipelines, into apps or agents built by business teams in plain language, and out as signed, cited results that compliance staff can trace. Rules are bound to a use case once; every app and agent that touches that use case inherits them without a developer re-implementing them.
The differentiating claim is governance as infrastructure rather than an afterthought. Prompt-injection attempts, PII, and policy violations are screened inside the pipeline — a blocked call never leaves the system. Every run is scored live against a golden set and watched for drift, with source tracing on every output. The vendor maps controls to ISO 42001, NIST AI RMF, the EU AI Act, and India’s DPDP, so a regulator asking for evidence gets a framework-aligned answer rather than a spreadsheet assembled under deadline pressure.
The tool fits regulated industries — banking and insurance in particular, where the vendor provides seeded, read-only demo consoles for both use cases — that need end-to-end control without stitching twenty separate tools together. The AGPL-3.0 open-source licence and self-host option mean no vendor lock-in: swapping a model or a gateway is a configuration change, not a migration project. Where it breaks: the plain-language app builder is designed for business teams describing straightforward use cases, and community patterns suggest conditional branching that requires multi-step logic quickly outgrows what non-technical builders can express without developer involvement.