ReN3
Enterprise agentic AI platform for building no code vertical agents over documents and content, with air gapped deployment and multi LLM accuracy.
ReN3 is an enterprise agentic AI work productivity platform based in Singapore that lets organizations build deep vertical agents for document and content workflows. The platform provides a no code agent builder for functions across administration, legal, finance, procurement, and human resources, and supports multimodal retrieval across 80 plus file formats including text, audio, and video. Core capabilities include knowledge retrieval, enterprise data analysis over structured and unstructured data, content and report generation, and process automation with visible audit trails. ReN3 uses a multi LLM architecture that lets clients run locally hosted models such as Llama, Mistral, and Deepseek entirely within their own infrastructure, and applies multiple accuracy techniques including cross model verification to reduce hallucinations. It is built for fully air gapped on premise, private cloud, and hybrid deployment with zero external dependencies, and is SOC 2 Type 2 certified. Early customers include HTX, SBS Transit, SM Prime, Monde Nissin, and NAT Re.
Vendor details
Canonical URL
https://www.ren3.ai
Category
Agent builder
Funding status
Seed. Raised 5 million dollars in a seed round led by Vertex Ventures Southeast Asia and India in May 2026.
Company status
private
Use cases & customers
Primary use cases
Target customers
Integrations
Integrates with enterprise business applications and existing access rights systems, with synchronized access controls and knowledge versioning, and processes 80 plus file formats including documents, audio, and video.
Sources & related URLs
Related / legacy domains
Research sources
Agentic Index coverage score
6.0 / 14 capabilities · 43%
| Integrations & Tool CallingIntegrates with enterprise business applications and existing access rights systems across 80 plus file formats, though specific named connectors are not detailed (ren3.ai, vertexventures.sg). | Partial |
|---|---|
| Workflow OrchestrationProvides no code creation of vertical agents with a planned agentic workflow builder to chain agents into auditable processes (ai-market-watch.com, technotrenz.com). | Partial |
| Knowledge Grounding & RAGMultimodal retrieval augmented grounding across 80 plus file formats including text, audio, and video is core to the platform (ai-market-watch.com, ren3.ai). | Full |
| Human Oversight & GuardrailsCross model verification and visible audit trails provide accuracy guardrails, though explicit human approval workflows are not detailed (technotrenz.com). | Partial |
| Security, Identity & GovernanceSOC 2 Type 2 certified with synchronized access rights and air gapped deployment for data sovereignty (technotrenz.com, vertexventures.sg). | Full |
| Observability & AuditabilityProvides visible audit trails and knowledge versioning, though dedicated observability tooling is not detailed (tracxn.com, ai-market-watch.com). | Partial |
| Memory & State PersistenceKnowledge versioning and auto retention are content management features; agent level memory or state persistence is not documented (ai-market-watch.com). | Unable to verify |
| Deployment & Data ResidencyDeploys fully air gapped on premise, in private cloud, or hybrid with zero external dependencies (vertexholdings.com, vertexventures.sg). | Full |
| Prebuilt Agents / Templates / PacksAn agent marketplace is planned but not yet shipped (technode.global). | Unable to verify |
| Triggers & Channel CoverageNo event trigger or channel coverage is documented (ren3.ai). | Unable to verify |
| Model Flexibility & RoutingMulti LLM architecture lets clients choose the model per task and run Llama, Mistral, Deepseek, and Whisper locally within their own infrastructure (technotrenz.com). | Full |
| APIs / SDKs / MCP ExtensibilityNo public API, SDK, or MCP extensibility is documented (ren3.ai). | Unable to verify |
| Testing, Debugging & OptimizationAccuracy techniques are internal to the platform; no user facing testing or evaluation tooling is documented (technotrenz.com). | Unable to verify |
| Browser / Computer-useNo browser or computer use capability is documented (ren3.ai). | Unable to verify |
The Agentic Index coverage score grades every vendor Full, Partial or Unable to verify against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded
Pricing
Not public. ReN3 is sold through an enterprise and channel partner motion with no published pricing.
Enterprise license; deployment and seat scope negotiated.
Included quota
Not public.
Cost watchouts
Self hosted GPU and infrastructure costs for locally run models; deployment and integration services.
Variable cost rationale
Air gapped and on premise deployments run locally hosted models on the customer's own GPUs, so model inference and infrastructure cost sits with the customer and scales with usage.
Overage / add-ons
Not public.
Sales call required
Yes, required for paid access
Free / trial
Not public.
Lowest paid plan
Not public.
Key ambiguities
No public pricing; license structure and minimums are not disclosed.
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Alternatives to ReN3
The closest documented capability profiles to ReN3 among agent builders tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.
- Moterra6.5 / 14Adds documented Prebuilt Agents, Templates & Packs
- Khoj8.0 / 14Adds documented Memory & State Persistence and Triggers & Channel Coverage, among others
- Cassidy7.5 / 14Adds documented Prebuilt Agents, Templates & Packs and Triggers & Channel Coverage, among others
- Cohere North7.5 / 14Adds documented Prebuilt Agents, Templates & Packs and Triggers & Channel Coverage, among others
- Moveo.AI7.0 / 14Adds documented Memory & State Persistence and Prebuilt Agents, Templates & Packs, among others
- Lyzr10.5 / 14Adds documented Prebuilt Agents, Templates & Packs and Triggers & Channel Coverage, among others
Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded