Inboxintel/docs/discovery/09-roadmap.md

09 — Product Roadmap (Phase 8)

Everything from discovery, split into releases and prioritised by user value vs engineering effort. The guiding sequence: ship the redesign + dramatically better (deterministic) search first, then layer optional local AI in value order, each tier reusing infrastructure the previous one built.

Update — multi-provider platform epic. The multi-provider + admin/settings design is a v1.x platform epic (its own 6-phase plan) that the search/AI features build on. Sequencing note: the provider abstraction, unified email model, settings, and feature-flag engine land early in v1.x (they underpin multi-user + AI gating); the AI features from this roadmap then plug into that flag system. Both plans share the same flag-gated, ship-dark discipline.

Prioritisation framework

Score each item Value (1–5) × (6 − Effort 1–5), then sequence so that (a) high-value/ low-effort ships first, (b) risky/expensive AI comes only after its infrastructure exists, and (c) nothing in an early release depends on AI being enabled.

 Value ▲   ★ MVP first        ● do next        ○ later
   5 │ ★ranking ★redesign     ●NL search       ○ask-inbox
   4 │ ★fuzzy ★chips ★summary ●semantic ●brief  ○knowledge graph
   3 │ ★perf/indexes          ●people ●extract  ○collaboration
   2 │                        ●categorise-tail  ○plugins ○mobile
   1 │                                          ○multi-provider
     └───────────────────────────────────────────────────►
        low effort ──────────────────────────► high effort

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MVP → v1.0.0 — "The redesign + world-class deterministic search"

Rationale: the single biggest perceived-quality jump, built mostly on deterministic tech (low risk). AI appears only as a few optional, reversible wins behind a toggle.

• UX v2 shell + design system + both themes (dark-first, green ramp) — the "world-class" feel.
• Search core: relevance ranking (RRF/ts_rank), multi-field weighted FTS, pg_trgm fuzzy, filter chips, saved/recent/suggested, "why matched" (lexical), keyset pagination.
• Perf/debt: pg_trgm + FTS indexes, virtualised list, code-splitting, fix EF query-filter warning, language-aware FTS.
• AI foundation: extended abstraction (IAiProvider+IEmbeddingProvider+facade+router), Null + Ollama wired, VRAM guard, prompt templates.
• First AI wins (optional): thread summary · follow-up detection (heuristic + AI confirm) · reply suggestions.
• Why now: delivers the flagship promise (fast, approachable, ranked, explainable search
  • a premium UI) even with AI off.

v1.1 — "Assisted search & productivity"

Rationale: build on MVP's embedding groundwork; assist without heavy compute.

• Natural-language search parse (rules-first + optional LLM), shown as editable chips.
• People search · attachment (filename) search · search-driven bulk actions.
• Inbox assistant / daily brief · task/calendar/reminder extraction.
• Categorisation long-tail (embedding zero-shot + confidence) · priority prediction v1.
• Why now: the "assisted, not syntactic" search vision, plus the highest-value AI productivity features — all still light on VRAM.

v1.2 — "Semantic tier"

Rationale: introduces pgvector + embedding backfill; unlocks meaning-based features.

• Semantic search (pgvector HNSW, hybrid RRF) · related / find-similar.
• Near-duplicate detection · thread summaries surfaced in results · conversation insights.
• Relationship mapping (basics).
• Why now: semantic recall is a headline differentiator but needs the embedding infrastructure and backfill worker to be mature and VRAM-safe.

v2.0 — "Ambitious AI"

Rationale: flagship, compute-heavy features that need a mature semantic + vision stack.

• Conversational "ask your inbox" (RAG + citations).
• Entity search & facets (amounts, orgs, dates) · attachment OCR/content understanding (vision, on-demand).
• Phishing reasoning (LLM over flagged mail, async, explained) · knowledge graph.
• Why now: highest wow-factor and the strongest "local private AI" story, but only worthwhile once retrieval, extraction, and vision infra are proven.

v3.0 — "Platform"

Rationale: expand beyond the individual power-user once the core is best-in-class.

• Collaboration / shared inbox (assign, comment) · automation / rules engine (a docs/specs/feature-rules-engine.md already exists — fold it in).
• Multi-account & additional providers (IMAP/Outlook) · plugin ecosystem (analyzer API) · mobile app · multi-window / desktop shell (Tauri) · multi-provider AI.
• Why now: platform bets that only pay off on top of a beloved core product.

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Sequencing principles (explained)

1. Deterministic value before AI. MVP's biggest wins (ranking, chips, redesign) need no AI — they de-risk the release and prove the product before compute-heavy features.
2. Infrastructure amortised. Embeddings introduced once (v1.1 foundations → v1.2 usage) power search, dedup, related, categorisation, and RAG — spread the cost.
3. Value-first within a release. Inside each version, highest value/effort ships first so partial delivery is still shippable.
4. AI is always additive. Every release is complete and excellent with AI disabled — protecting the "works without AI" mandate and the mainstream audience.
5. Platform last. Collaboration/plugins/mobile are large and only worthwhile once the individual experience is genuinely best-in-class.