Orchestrate the right models, verify every answer, and own the outcome.
Annie is the model orchestration layer for sovereign AI. Multiple specialist models, verified through independent consensus, fine-tuned on your data, deployed on infrastructure you control. Built for the work that can't afford to be wrong.
Built for high stakes work. Deployed on sovereign infrastructure.
You don't need a monolithic, all-knowing model. You need the right expert, for the right task, verified and yours.
The frontier labs built extraordinary token predictors at planetary scale. But they are economically unsustainable, geopolitically fragile, and architecturally mismatched to the work enterprises actually need done. Research is converging on a conclusion they don't want to hear: small, domain-tuned specialist models, verified by independent peers and deployed on infrastructure you control, outperform general-purpose giants — at a fraction of the cost.
Annie is that architecture, productised.
One request, eight stages, a verified answer
Frontier models hand you one black-box guess. Annie runs every request through a pipeline you can see — and trust. Scroll to follow a single request, stage by stage.
It reads the whole problem first
Every request is parsed for intent, context and sensitivity before a single model runs. Annie knows exactly what's being asked — and how much it matters — from the outset.
No assumptions, no blind spotsThe right experts, not one guessing giant
Instead of forcing one monolithic model to know everything, Annie classifies the task and routes it to the precise specialists equipped to handle it.
Specialist precision beats generalist guessingGrounded in data that never leaves your walls
Before the experts respond, they're grounded in your own knowledge base — air-gapped on infrastructure you control. No external API. No data crossing your perimeter.
Sovereign by architecture, fully air-gappableYour models, working in parallel
Domain specialists run side by side — your risk model, your classified specialist, your clinical model. Each one is yours, plugged into the pipeline and orchestrated by Annie.
Bring your own models, keep your edgeAnswers are weighed, not assumed
The Judgment Panel compares the experts against one another. Where they disagree, the conflict is surfaced — not silently averaged away. Consensus has to be earned.
Disagreement surfaced, not buriedNothing ships unverified
Every claim is independently checked against your sources before it leaves the pipeline. If an answer can't be verified, it doesn't go out — the difference between confident and correct.
Verified output on every decisionA verified answer, fully auditable
The response leaves with its reasoning and provenance intact — traceable end to end. You don't just get an answer; you get the evidence behind it.
Auditable from question to answerAnd overnight, it gets better
In off-peak cycles, the Cognition Stream refines your models on the day's work — starting at $5 a run. No million-dollar retraining, no waiting on a provider. A flywheel that compounds while you sleep.
The flywheel, not retrainingThat's Annie — the whole pipeline, working as one
One request, eight stages, your models: classified, grounded, deliberated, verified and delivered with the evidence intact — then quietly improved overnight. The pipeline you can see, on infrastructure you control.
Verifiable AI, sovereign by designAnnie's advantage is not a feature — it is architectural. Three compounding advantages that frontier models cannot replicate.
Plug in your domain knowledge. Annie verifies it before responding. You keep your competitive advantage. The platform orchestrates it.
Your models improve automatically on your data, in off-peak cycles, starting at $5 per run. No million-dollar retraining bills. No waiting for a provider.
10–100× lower inference cost than frontier APIs at enterprise scale — because the architecture is built for efficiency, not scale-at-any-cost.
How you run a model matters as much as the model itself
Annie is not just a model. It is a verified AI orchestration platform — a system of open pipeline roles (twelve today, expanding as customer deployments grow) designed to classify, route, judge, and verify expert responses. Annie ships with our own sovereign foundation workforce models which can be retrained to match your needs. A bank brings their own risk model. A defence contractor plugs in a classified domain specialist. A health service adds a clinical decision model. Each runs through the same classification, consensus, and verification pipeline. The platform provides the infrastructure and orchestration. The models are yours.
Open pipeline roles — twelve today. Bring your own models, your own domain knowledge, your own competitive advantage. Annie orchestrates them.
Every model's output is cross-checked by independent peers using domain rubrics, then verified against the original prompt. Hallucination is a managed risk.
Cognition Stream continuously fine-tunes your specialist models on your own data — no manual retraining cycle. The longer Annie runs, the more precisely it reflects your organisation.
Access to our Workforce Foundation Models means you focus on domain context. We handle the rest.
The Workforce Foundation Model suite is not just a pre-trained model — it is a collection of sovereign, heterogeneous models optimised for the hierarchical mixture of experts architecture. This means you can bring your domain knowledge, your business context, the data that makes your model yours, without starting from zero. This is what separates fine-tuning on Annie from fine-tuning on a frontier API or an open-source base. The verification pipeline is already built in.
Domain-specific fine-tuning on your data, not training from scratch. Weeks to deployment, not months.
Fine-tuning runs can start at $5 per iteration — continuous improvement without the million-dollar retraining bill.
Your custom model benefits from the verification pipeline and peer consensus by design — not just raw parameter count.
You bring the domain knowledge. We provide the foundation, the orchestration, and the verification pipeline. The result: custom AI that is accurate, auditable, and deployed in weeks.
Annie is the only enterprise AI platform where you plug in your own models and keep your competitive advantage.
Open pipeline roles — twelve today, with the architecture designed to add more as deployments grow. Evari provides the foundation models as proof of concept, but every slot is replaceable. A bank's proprietary risk model runs alongside Evari's general models. A defence contractor's classified specialist never leaves their infrastructure.
Multi-model consensus and verification is built into the platform, not bolted on as a feature.
Every expert response is scored by a Judgment Panel using domain rubrics, verified against the original prompt, and re-routed if it fails. Hallucination reduction of 4–67% vs. single-model approaches. Calibration error reduced by 49–74% across medical benchmarks.
Your models improve on your data automatically, in off-peak cycles, starting at $5 per run.
Every interaction flows through the Cognition Stream. Sleep cycles fine-tune specialists on real user data. No manual retraining. No million-dollar bills. No waiting for a provider to release a new version.
10–100× lower inference cost than frontier APIs at enterprise volume — because the architecture is built for efficiency, not scale-at-any-cost.
Specialists run on standard inference GPUs. Intelligent routing directs 80–95% of queries to the most cost-efficient path. Multi-model consensus costs less than single-model inference at frontier scale.
| Volume | Annie | Frontier API |
|---|---|---|
| 100M tokens/day (annual) | $18K – $73K | $550K – $1.8M |
Every component deploys on infrastructure you control. No external API calls. No data leaves your jurisdiction. No single point of failure.
Base model trained from scratch — no dependency on external weights. Fully air-gappable. Every model, every inference step, every verification decision runs on your hardware. Provider outages, export controls, geopolitical events, and platform decisions made in another country's parliament — none of these reach you. Sovereignty is not a feature. It is the consequence of building the architecture correctly.
Sovereign AI for high-classification environments. Annie can be deployed fully air-gapped with no external API calls, supports PROTECTED workload certification, and is designed for Five Eyes interoperability requirements. Every inference stays on sovereign infrastructure.
APRA-regulated environments demand domain precision and a complete, auditable decision record. Annie fine-tunes specialist models on your own data — underwriting, claims, compliance, risk — and the Judgment Panel produces verified output with full reasoning chains for every decision.
Patient data must stay sovereign. Clinical outputs must be accurate and explainable. Annie deploys on-premises within your existing infrastructure, fine-tunes on your clinical data without it ever leaving the boundary, and produces explainable reasoning chains suitable for clinical review.
Jurisdictional data control is non-negotiable across legal, regulatory, and compliance functions. Annie's Judgment Panel verifies every output against defined rubrics, producing a traceable chain of reasoning that can withstand professional scrutiny — whether that's a legal opinion, a compliance sign-off, or a regulatory submission.
Annie runs on sovereign infrastructure. We are looking for Australian operators positioned to host the workload.
Annie is the application layer built for the sectors that need sovereign infrastructure most — government, defence, financial services, healthcare. Each enterprise customer brings their own models, runs them through Annie's verified pipeline, and consumes inference on your racks. More customers means more models means more racks consumed. The full partnership model, deployment fit, and engagement process is on the dedicated page.
Annie is powered by QuivaWorks — the agentic AI builder platform from Evari. QuivaWorks provides the orchestration, routing, and workflow infrastructure that makes Annie's platform architecture possible, and is available independently for organisations building their own AI-native workflows.
Explore QuivaWorks at quiva.ai →AI that's yours. Completely.
Built for high stakes work. Deployed on sovereign infrastructure.