Augure vs Google Vertex AI in Montréal: regional endpoints, read closely

Vertex AI is Google Cloud's managed platform for Gemini, partner models such as Claude, and open models; Google now calls it Gemini Enterprise Agent Platform. It has a Montréal region, northamerica-northeast1, and suits teams already on Google Cloud with VPC Service Controls and CMEK. Augure is a Canadian AI platform and OpenAI-compatible API for regulated Canadian work, with customer data stored in Canada and inference never routed to providers in the United States. The biggest difference is what a region selection actually commits to: on Vertex AI the Canada processing commitment is per model and absent for the newest Gemini models, while Augure's residency is a property of the account. Privacy officers, platform teams and developers should read this before choosing.

At a glance

	Augure	Google Vertex AI in Montréal
Company and jurisdiction	Canadian company, no US parent or investors.	Google Cloud, under the Google Cloud Platform Terms of Service, per its data governance page.
Where customer data is stored	Canada.	Data stored at rest in the customer-selected location remains in that location, regardless of the endpoint called, per Google.
Where inference runs	Canadian infrastructure (Ontario) and vetted EU partners under zero-data-retention; never US providers.	Regional endpoint: within the country or multi-region jurisdiction for models that list the commitment. Global endpoint: any Google Cloud location worldwide.
Your data used for training	Never.	Google states it will not use your data to train or fine-tune models without your prior permission or instruction.
Canadian residency option	Storage always in Canada. Accounts can be set Canada-only: requests then stay in Canada or fail with 503 residency_unavailable, never served elsewhere. tofino-3 and the Augure Open models never leave Canada.	Use northamerica-northeast1 with a model that carries the Canada ML-processing mark: Gemini 3.5 Flash, 2.5 Flash, 2.5 Pro and two embedding models as of October 2026. Claude and open models have no Canada column.
Prompt retention	Prompts never logged by Augure.	Caching is on by default and cleared within 24 hours; Google may log prompts for abuse detection under the Cloud Platform Terms; zero data retention requires customer configuration.
API	OpenAI-compatible, https://api.augureai.ca/v1	Gemini API via google-genai SDK or REST, project and location scoped.
Models	ossington-5 (256K), rosedale-1 (up to 1M), tofino-3, Augure Open (GLM-5.3, Qwen3.8-Flash-Next)	Gemini 4 Argon, 3.8, 3.7, 3.6, 3.5, 3.1, 2.5 families; Claude 4.x and 5.x; Mistral; Grok; DeepSeek, GLM, Qwen, Llama and gpt-oss open models, all listed for Montréal.
Security controls	TLS 1.3 in transit, AES-256 at rest.	Data residency at rest, CMEK, VPC Service Controls and Access Transparency listed per Gemini model; not supported for preview models.
Tools, images, PDFs	Function calling, streaming, image and PDF input, response_format json_schema.	Multimodal input (text, image, video, audio) priced per model; tool calling and grounding features.
Languages	English and Quebec French natively.	Multilingual models; Quebec French not addressed on the Google pages checked for this comparison.
Billing currency	CAD.	USD; non-global endpoints cost 10 percent more for Gemini 3 and later.
Best fit	Canadian organisations that need Canadian operation and jurisdiction without a cloud estate.	Google Cloud shops that want Gemini plus partner and open models under one project.

Where Vertex AI wins

• Catalogue in Montréal. Google's locations page lists Gemini 4 Argon through Gemini 2.5, Claude Haiku, Sonnet, Opus and Fable 5.x, Mistral, Grok, DeepSeek, GLM, Qwen, Llama and gpt-oss for northamerica-northeast1.
• Multimodal breadth. Gemini models take text, image, video and audio input, with image generation, Veo video, Chirp speech and embedding models in the same region.
• Google Cloud controls. CMEK, VPC Service Controls and Access Transparency are listed per Gemini model for online prediction, batch and context caching.
• Price on light models. Gemini 2.5 Flash is listed at US$0.30 input and US$2.50 output per million tokens; Gemini 3.5 Flash-Lite at US$0.30 and US$2.50 on the global endpoint. Augure's lightest tier, tofino-3, is C$0.60 and C$2.00.
• Zero data retention is configurable. Google documents the switches: leave request logging off, set store = false, disable caching and skip session resumption.

Where Augure wins

• Canadian company and jurisdiction. Augure has no US corporate parent and no US investors. Customer conversations, documents and AI inference are never handled by US-jurisdiction providers, so the CLOUD Act's reach over US-controlled providers does not extend to customer content.
• Residency by account, not by model. Inference runs on Canadian infrastructure and with vetted EU partners under zero-data-retention agreements, never US providers. A Canada-only account fails closed rather than serving elsewhere, and every response reports inference_region.
• Newest models included. On Vertex AI the Canada ML-processing mark is missing for Gemini 4 Argon and the 3.8, 3.7 and 3.6 Flash models as of October 2026. Augure's flagship ossington-5 and 1M-context rosedale-1 are covered by the same residency rules as every other tier.
• No prompt logging and nothing to switch off. Prompts are never logged by Augure and never used for training. There is no default cache or abuse log to configure away.
• Quebec French and CAD. Models are built for Canadian law and Quebec regulatory context. ossington-5 is C$1.50 input and C$3.00 output per million tokens; rosedale-1 is C$2.50 and C$6.00. No Google Cloud project, IAM binding or regional surcharge.

Switch from Vertex AI to Augure

1. Create a key at https://augureai.ca/developers. Keys look like aug_sk_live_... and are shown once.
2. Change the client. Replace genai.Client with an OpenAI-compatible SDK pointed at https://api.augureai.ca/v1 with Authorization: Bearer <key>. Project, location and Google credentials go away.
3. Map model ids.

Vertex AI model	Augure model	Why
Gemini 4 Argon, Gemini 2.5 Pro	ossington-5	Reasoning tier, 256K context, fastest of Augure's reasoning models.
Gemini with inputs over 256K tokens, agent loops	rosedale-1	Up to 1M context and Augure's recommended model for tool calling.
Gemini 3.x and 2.5 Flash, Flash-Lite	tofino-3	Fast tier, thinking off, served in Canada with no failover outside Canada.
Claude Sonnet, Opus or Fable on Vertex	ossington-5 or rosedale-1	Same reasoning tiers; pick rosedale-1 for long documents.
GLM 5, Qwen3 open models	open-glm-5-3 or open-qwen-3.8-flash-next	Augure Open serves open-weight models in Canada, messages reach the model as sent.
Unsure	auto	The gateway picks per request.

4. Before and after in Python. Google's current google-genai README creates the client with enterprise=True; if your code predates the rename, the shape of the change is the same.

import os

# Before: Vertex AI / Gemini Enterprise Agent Platform (google-genai)
from google import genai
client = genai.Client(
    enterprise=True,
    project=os.environ["GOOGLE_CLOUD_PROJECT"],
    location="northamerica-northeast1",  # "global" would allow processing anywhere
)
resp = client.models.generate_content(
    model="gemini-2.5-pro",
    contents="Summarise this contract in two lines.",
)
print(resp.text)

# After: Augure
from openai import OpenAI
client = OpenAI(base_url="https://api.augureai.ca/v1", api_key=os.environ["AUGURE_API_KEY"])
resp = client.chat.completions.create(
    model="ossington-5",
    messages=[{"role": "user", "content": "Summarise this contract in two lines."}],
)
print(resp.choices[0].message.content)
print(resp.model_extra["_augure"]["inference_region"])

5. Re-check these settings.
   • Request shape: contents becomes a messages list with roles; system instructions become a system role message.
   • max_tokens: Augure caps output at 32,768 tokens (tofino-3: 16,384). Omit it on reasoning models so thinking does not starve the answer.
   • reasoning_effort: none turns thinking off on ossington-5 for mechanical tasks; rosedale-1 serves none as low. Gemini thinking budgets have no direct equivalent.
   • response_format: json_object and json_schema are supported; validate and retry once on reasoning models, and do not combine with tools there.
   • Tool calling: Gemini function declarations become the OpenAI tools array; results return as role: "tool" messages. Pin rosedale-1 for agent loops.
   • Streaming: stream: true returns Server-Sent Events; add stream_options: {"include_usage": true} for a usage chunk.
   • Grounding with Google Search, RAG Engine, context caching and video or audio input do not carry over. Augure offers PDF and image input, link reading and a separate /v1/search endpoint.
6. Run both for a week. Compare answers on real traffic, log _augure.request_id, then cut over by changing the client and the environment variables.

Keep Vertex AI if

• You need Gemini specifically, or video, audio, image generation or speech models in the same project.
• Your workloads use Gemini 2.5 Pro, 2.5 Flash or 3.5 Flash on the regional endpoint, and the published Canada ML-processing commitment satisfies your privacy officer.
• Your controls depend on VPC Service Controls, CMEK, Access Transparency or Google Cloud IAM, and your auditors expect them.
• You rely on Grounding with Google Search, RAG Engine or Flexible Savings Plans.

Sources

• https://docs.cloud.google.com/vertex-ai/generative-ai/docs/learn/locations (checked 2026-10-27, page updated 2026-10-26): Montréal (northamerica-northeast1) model list; "Endpoints don't guarantee data residency or in-region ML processing"; global endpoint benefits and caveat; locations/global URL form.
• https://docs.cloud.google.com/vertex-ai/generative-ai/docs/learn/data-residency (checked 2026-10-27, page updated 2026-10-26): data at rest stays in the selected location; locational endpoints keep ML processing within the country or multi-region jurisdiction; global endpoints give no residency guarantee; per-model Canada column marks.
• https://docs.cloud.google.com/vertex-ai/generative-ai/docs/data-governance (checked 2026-10-27, page updated 2026-10-26): no training without permission; caching on by default and deleted within 24 hours; abuse logging under the Cloud Platform Terms; zero data retention steps.
• https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/security-controls (checked 2026-10-27, page updated 2026-10-26): data residency at rest, CMEK, VPC-SC and Access Transparency per Gemini model; not supported for preview models; partner and open model prompt logging off by default.
• https://cloud.google.com/vertex-ai/generative-ai/pricing (checked 2026-10-27): prices in USD; Gemini 2.5 Flash, 2.5 Pro, 3.5 Flash and 3.5 Flash-Lite rates; non-global endpoint pricing for Gemini 3 and later from July 1, 2026; introductory and promotional pricing notes.
• https://github.com/googleapis/python-genai (checked 2026-10-27): genai.Client(enterprise=True, project=..., location=...), generate_content and response.text; "Gemini Enterprise Agent Platform (formerly Vertex AI)".
• https://augureai.ca/docs/api, https://augureai.ca/docs/models, https://augureai.ca/docs/agents, https://augureai.ca/docs/integrations/openai-python, https://augureai.ca/llms.txt (Augure facts, prices in CAD).