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AI Architect Academy

A1 · Grounded assistance · professional services, life sciences, public sector, financial services, manufacturing

Grounded research desk

Answers that cite the exact passage, or say they cannot.

Customer job
Find a defensible answer in policies, research reports and filings without reading forty documents.
Today
Analysts search shared drives and intranet pages, read in full, and paste excerpts into notes; answers vary by analyst and sources are rarely recorded.
Accepted result
An answer the analyst forwards without rework, with each claim traceable to a passage they are permitted to see.

Realization

Agent Search with Gemini 3.8 Flash on Cloud Run

Analysts ask questions of a governed corpus and receive answers in which every claim links to a retrieved passage the asker is allowed to read. Unsupported questions are refused, not guessed.

Google Cloud / primary provider

What carries each step.

Agent Search handles hybrid retrieval and permission-aware indexing; RAG Engine covers custom chunking. Keep the corpus in Cloud Storage with object-level IAM mirrored into index metadata.

Data and model estate in one place: Gemini on Agent Platform, Agent Search and RAG Engine, AlloyDB and BigQuery, Cloud Run for everything else.

ComponentServiceEvidence
Person
Cloud Runprior, ga
Identity-Aware Proxyprior, ga
Cloud Runprior, ga
Apigee (AI gateway policies)prior, ga
Gemini 3.8 Flash (Agent Platform)source, ga
Agent Searchsource, ga
RAG Engine (Agent Platform)source, ga
Cloud Storageprior, ga
Firestoreprior, ga
Cloud Logging, Monitoring, Traceprior, ga
Evaluation service (Agent Platform)confirm

Customer view / judgement, not benchmark

Weigh what this customer values.

Remove providers that fail a hard constraint first: residency, data rights, identity estate, latency, operating owner, budget. Then weigh the rest. Scores are architect judgement on a 1-5 scale for the pattern as specified, recorded with a rationale. They are not benchmarks. A provider's consumption opportunity never changes a customer score.

Highest weighted: Vercel, 4.33 of 5.

  1. Performance 4Time to value 5Speed to execution 5Cost per accepted result 4Exit cost 5Governance fit 3

    Model and data layers stay swappable; enterprise identity, residency and audit depend on the chosen Marketplace partners.

  2. Performance 5Time to value 4Speed to execution 4Cost per accepted result 5Exit cost 3Governance fit 4

    Edge latency and low request cost; AI Search is remote-only in development and its permission model must be validated per corpus.

  3. Performance 4Time to value 4Speed to execution 4Cost per accepted result 3Exit cost 3Governance fit 5

    Managed retrieval with permission controls and residency options; index and model tie the workload to Agent Platform, which raises exit cost.

  4. Performance 4Time to value 4Speed to execution 3Cost per accepted result 3Exit cost 3Governance fit 5

    Strong account-level controls; more services to wire than the primary platforms.

  5. Performance 4Time to value 4Speed to execution 3Cost per accepted result 3Exit cost 3Governance fit 5

    Best fit where documents already live in SharePoint and identity is Entra; search unit pricing is step-shaped.

  6. Performance 3Time to value 3Speed to execution 4Cost per accepted result 4Exit cost 5Governance fit 2

    Lowest lock-in; identity, audit and guardrails are custom work.

Provider ledger / shown after the choice

What grows on Google Cloud.

These meters are the provider team’s consumption view. They explain the cloud workload; they never raise a customer score.

  • Gemini input and output tokens
  • Cloud Run vCPU-seconds and requests
  • Agent Search queries and index storage
  • AlloyDB or Cloud SQL instance hours
  • BigQuery slots or bytes scanned

Take it with you / generated from one specification

Exact views, and a running start.

Google Cloud views

Every provider

One-click template / ai-architect-answer/v1

Grounded answers on Cloud Run with Gemini 3.8 Flash on Agent Platform

Model: gemini-3.8-flash on the global endpoint. Auth: Service account Application Default Credentials.

Evidence: local-tested: conformance suite, installed @google/genai client options and a local server run in fixture mode. Not yet verified: Container build, Cloud Run Button flow and a live Gemini call. The button builds from the engine’s main branch.

Customer ledger / assumptions you can move

Cost per accepted result.

Every attempt is charged, so failed runs count. Value comes only from accepted results. Illustrative assumption for a 120-analyst team; replace with measured volume and baseline time before any business case.

Primary metric: Accepted cited answers per analyst hour. Answers marked forwarded or reused without edit, divided by analyst hours spent in the workspace.

Monthly value
€54,000
Monthly cost
€2,680
Net
€51,320
Cost per accepted result
€1.12

Experience / drawn from the specification

What the person sees, including no.

Screens are rendered from structured blocks in the catalog, so a refusal or an exception is designed before it happens. Values marked fixture are illustrations, not measurements.

What do you need to know?

Contracts libraryProcurement policy 2026My permissions: Legal, Procurement

Searches only documents you can open.

Askdesktop · default

Three active contracts allow termination for convenience below 60 days: Northwind Logistics (30 days) [1], Contoso Packaging (45 days) [2], and Fabrikam Metals (30 days, only after year one) [3].

  1. MSA Northwind s.14.2
  2. Contoso SoW-7 s.9
  3. Fabrikam MSA s.11.1
Open passageForwardFlag

3 claims, 3 passages, 2.8 s. Fixture data.

Cited answerdesktop · success

No passage you can access answers this question.

  • Closest: Procurement policy 2026, section 4 (termination rules)
  • Ask the contracts team to add the 2024 amendments
Request a source
Not in the corpusdesktop · refusal

Notice period in the Northwind MSA?

30 days for convenience, 10 days for cause [1].

[1] MSA Northwind s.14.2
Answer on the movemobile · success

Team workflow / who carries what

Every lane leaves evidence.

LaneResponsibilityEvidence it leaves
CustomerAsk, read the cited answer, forward or flag itForward and flag events in the ledger
AIDraft from passages; return passage IDs per claimCitation coverage per answer
SystemFilter by permission, enforce budget, log every callTrace with scope and token count
ReviewerKnowledge owner reviews flagged answers weekly and fixes the sourceClosed flags with source revision
OperatorWatch refusal rate, cost per accepted answer and stale-source alertsWeekly dashboard export

Release evaluations

What must pass before anyone ships.

  • Citation precision

    >= 0.95 of claims map to a retrieved passage that supports them

    Frozen set of 200 questions with expected passages; scorer checks each claim span.

  • Must-refuse accuracy

    >= 0.90 refusal on 50 out-of-corpus questions

    Negative set built from questions owners confirmed are unanswerable.

  • Permission leak

    0 passages returned outside the caller's permissions

    Adversarial personas with restricted groups.

  • Answer latency

    p95 <= 6 s end to end

    Gateway telemetry over the frozen set.

Risks and controls

What would go wrong first.

  • Answers cite superseded document versions.

    Source revision stored per citation; re-index triggers review of affected answers.

  • Instructions hidden in a document steer the model.

    Passages are quoted as data; tool use disabled; output limited to passage-backed claims.

  • Retrieval bypasses permissions.

    Permission filter applied in the index query, tested with adversarial personas.

Image recipes / concept art only

When to generate, and when never to.

16:9 · gpt-image-2 or a current Gemini image model

Customer moment for a proposal cover or portal hero.

Cinematic editorial photograph, late afternoon light, shallow depth of field. Find a defensible answer in policies, research reports and filings without reading forty documents. The moment just after the accepted result: An answer the analyst forwards without rework, with each claim traceable to a passage they are permitted to see. Real workplace, restrained palette of deep navy, warm paper and one cobalt accent. Natural expressions, no screens facing the camera. Concept art only. Do not render product logos, cloud icons, UI text or architecture labels; compose exact labels from the specification in code.

3:2 · gpt-image-2 (consistent characters across panels)

Team workflow storyboard for a workshop or executive briefing.

Five-panel storyboard, clean ink line with flat colour, consistent characters across panels. Panels follow the lanes customer, ai, system, reviewer, operator: (1) Ask, read the cited answer, forward or flag it (2) Draft from passages; return passage IDs per claim (3) Filter by permission, enforce budget, log every call (4) Knowledge owner reviews flagged answers weekly and fixes the source (5) Watch refusal rate, cost per accepted answer and stale-source alerts Each panel shows hands and decisions, not screens. Concept art only. Do not render product logos, cloud icons, UI text or architecture labels; compose exact labels from the specification in code.

Do not generate

Any image a customer will read for component names, data classes or provider services.

Do not generate. Export the compiled view for the chosen provider. A generated architecture image can invent services, misspell names and draw icons the vendor never published.

A design, not a deployment: no realization on this page carries a provider receipt. Generated from the pattern source at revision c43825efda38. Apache-2.0 for catalog content and exports; provider names are trademarks of their owners; Google Cloud icons retain Google rights.

Next pattern: In-product copilot