Features

Features built for the people who actually use them

192 pre-built vertical AI agents · governance built into the runtime · works with your existing AWS, Azure, or GCP substrate.

Grouped by who actually uses them. Each card leads with the takeaway — scan the headline, read the detail only if you need it.

For business leaders

What makes pilots successful.

What makes board reports defensible, and what makes your business teams say yes.

Enterprise Context Engine, pre-built

Most platforms make you spend 6–12 months building the semantic context layer yourself. We ship it pre-built — agents activate in days, not a 3-month data project each.

145 canonical metrics

7 industries

37 entity types

Metrics span SaaS, FinServ, Healthcare, Industrial, B2B Services, Retail & CPG
37-type business entity ontology and org-structure model, pre-modeled
Pointer-only knowledge connectors for Box, SharePoint, Google Drive, Confluence & Notion — your data stays where it lives
Compliance inheritance: SOX, PII & GDPR tags propagate automatically

Activate proven agents, don’t author them

You’re not building agents on a blank canvas — you’re activating named agents already running in production today.

192 templates to remix

9 business functions

T0–T4 safety tiers

Live across Sales, Order Operations, Pricing & Promo, Catalog & Content, Customer Service, B2B Commerce, B2C / DTC Commerce, Quality Assurance, and Channel & Partner
Each ships a documented spec-card, value commitment & connector requirements
Tier-classified T0–T4 by side-effect blast radius

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Outcomes in your CFO’s language

Every agent run is measured in the KPIs your CFO already reports — NRR, AHT, fulfillment SLA, margin — never “tokens consumed.”

Value-chain dashboard shows runs, human time saved, and dollars in measurable outcomes
Board-ready PDF reports generate in one click
Auto-posts to your Slack channel for quarterly reviews

Human-in-the-loop where it matters

Agents never autonomously break things. Tier-based approvals route every sensitive decision to the right person.

Routine exceptions → process owner; permission grants → IT lead; policy changes → business sponsor
Approve or reject inline from Slack — no context switching
Full audit trail on every decision

Your AI investment, not ours

Multipliers runs on the AI substrate you already pay for — a process operating layer that uses your stack, not another stack to buy.

Works with AWS Bedrock, Google Vertex AI, Azure AI Foundry, or direct lab APIs (Anthropic, OpenAI, …)
Procurement counts toward your existing cloud commit (EDP / MACC / committed-use)
No model lock-in — we extend the labs and hyperscalers, never replace them

FDE-led deployment, not a SaaS to figure out alone

A dedicated Forward Deployment Engineer scopes, wires & operationalizes your agent fleet alongside your teams.

Most enterprise AI pilots stall at coordination, not technology
The FDE bridges your business sponsor, process owner & IT lead

How we engage

For IT leaders

The architectural decisions that make this safe to deploy.

And the operational guarantees that make it safe to scale in your environment.

Tenant-isolated semantic context layer

A context layer, not a data lake — cross-tenant isolation enforced structurally at the query layer.

Pointer-only sync by default; three permitted modes (pointer, cached_sample ≤60s/≤100MB, metric_compute_only) — bulk ingest doesn’t exist in the type system
37-type ontology with deterministic NER + relation extraction; LLM augmentation on a deterministic safety floor
Multi-hop graph traversal, probabilistic entity resolution, lineage to source on every fact

5-contract runtime — agents born compliant

Every hosted agent satisfies five mandatory runtime contracts, enforced at the publish gate.

MCP server · A2A AgentCard · MVE value outcomes · Context Engine integration · value-chain bindings
Non-compliant agents can’t reach production (hard-mode locked)
Governance dashboard shows per-agent compliance across all six pillars

Multi-tenant isolation at the query layer

Every database read and write filters by tenant_id as the first predicate.

Assertion-tested via captured-query introspection in every CI run
Cross-tenant probes return 404 — never leak existence
Cross-tenant test matrix runs nightly across all stacks

Cross-stack OAuth runtime

Unified OAuth with PKCE and refresh coordination — we handle credential lifecycle so you don’t.

One runtime across all four integration patterns (ingestion, enterprise platforms, knowledge/RAG, MCP targets)
Refresh coordination per tenant + platform + connection; atomic single-use state in DB (multi-instance safe)
Audit-trail uniformity across every connection

WorkOS enterprise SSO + SCIM

Enterprise SSO and SCIM directory sync across ~30 identity providers via WorkOS.

Okta, Azure AD, OneLogin, JumpCloud, Google Workspace & more
SCIM 2.0 directory sync via WorkOS-hosted endpoint
Email-domain → tenant routing with structural account-takeover defense

Substrate-agnostic compute distribution

Your AI, tools & sidecars run on your cloud — one codebase serves every deployment model.

AI on your Bedrock / Vertex / Foundry / direct lab; tools on your Lambda / Azure Functions / Cloud Run
Sidecars on your SageMaker / Azure ML / Vertex AI endpoints
Regulated industries: full VPC self-host on your EKS / AKS / GKE

Webhook trigger registry

Per-tenant inbound triggers with HMAC SHA-256 signature verification.

Triggers from Salesforce Flow, ServiceNow Business Rule, GitHub Actions & custom systems
Timing-safe verification, auto-derived idempotency keys, per-tenant rate limits
Secret rotation via admin UI

Replay for regression & compliance audits

Re-run any prior agent run against current code, policy & spec-card.

Side-by-side diff shows spec, policy, output & cost deltas
Replay events emitted to the Context Engine event log for audit trail

Audit events on every state change

Every state change logged to an audit trail with PII-clean payloads.

Approvals, agent runs, spec publishes, OAuth events & report generation captured
IDs, counts & status codes only — never user content
Configurable retention, exportable for SIEM ingestion

Per-tenant API tokens + scope model

Programmatic integration without sharing user credentials.

SHA-256-only-at-rest, scope-bound (outcomes:write, embedded_ui, …)
Optionally agent-bound, configurable TTL, instant revocation
Rate-limited per token

Shared platform foundations

Architectural commitments both audiences should know about.

No vendor lock-in

We extend Bedrock, Vertex, Foundry, and direct lab APIs — never compete with the model labs or hyperscaler AI platforms.

No per-client code

Per-customer variation is data, not code. Onboarding a new system = inserting a row. Cheaper to operate, faster to upgrade for everyone.

Idempotent by default

Every write is protected by idempotency keys. Webhook retries and marketplace re-deliveries are always safe.

Open protocols

MCP and A2A open specs. Your governance data exports to any BI tool; your agents are discoverable by any MCP client.

See it for your processes

30-minute discovery call. We’ll map your existing AI substrate, the processes you’d activate first, and the connectors we’d wire in your pilot.

Email contact@kiwana.ai

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