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 comprehensive audit trails and citation backed accuracy grounded in enterprise knowledge.
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. The company describes intelligent model routing as a way of optimizing cost, and reports a 67 percent reduction in token spend.
It is built for fully air gapped on premise, private cloud and sovereign deployment with zero external dependencies, with governance and multi tier access controls built into every AI interaction. ReN3 displays a SOC2-Compliant accreditation badge on its site. It publishes no certification type, scope, auditor or report.
The company reports more than 50 deployments. Named customers include HTX, SM Prime, NAT Re, Mizuho, AEON Credit Service and Ajinomoto, and it works through a partner channel that includes Red Hat, Dell, NTT, AWS, Microsoft, Lenovo, Nutanix, Google, Alibaba, Cisco and Capgemini. ReN3 was named to the Forbes Asia 100 to Watch 2026 list. The legal entity is The Reentry Foundation Pte Ltd.
Vendor details
Canonical URL
https://www.ren3.ai
Category
Agent builder
Funding status
Seed. Raised $5m led by Vertex Ventures Southeast Asia & India, announced 5 May 2026, with funds directed at the channel partner network, an agentic workflow builder and an upcoming agent marketplace. Founded 2021 in Singapore by Lemuel Low, Edmund Tan and Dennis Sze; team of 11-50. The legal entity is The Reentry Foundation Pte Ltd. Named to the Forbes Asia 100 to Watch 2026 list, cited for enabling sovereign AI deployment while optimizing costs through intelligent model routing. Reports more than 50 deployments. Named customers include HTX (Singapore's Home Team Science and Technology Agency), SM Prime, NAT Re, Mizuho, AEON Credit Service and Ajinomoto, with SBS Transit and Monde Nissin named in the funding release. Sold through a partner channel including Red Hat, Dell, NTT, AWS, Microsoft, Lenovo, Nutanix, Google, Alibaba, Cisco and Capgemini, and accredited by IMDA with a Meta Business Partner badge.
Company status
independent
Use cases & customers
Primary use cases
Target customers
Deployment options
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.
In practice
Your legal team wants contracts reviewed and summarized without writing code. ReN3 lets business users build that agent in its no code builder, and every answer is grounded in enterprise knowledge with citations and audit trails.
Your regulated business cannot send documents or prompts outside its own servers. ReN3 runs On-Premise on air gapped servers, with locally hosted models such as Llama, Mistral and Deepseek inside your infrastructure.
Your finance team asks questions across PDFs, spreadsheets, scanned images and audio. ReN3 routes each request by reasoning complexity, latency, enterprise policy and token cost, and reports a 67 percent reduction in token spend.
Sources & related URLs
Related / legacy domains
Research sources
Agentic Index coverage score
6.0 / 14 capabilities · 43%
| Integrations & Tool Calling | Partial |
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The platform connects documents, emails, websites, databases, enterprise applications and multiple file formats into a unified knowledge layer, with access rights synced from source systems. ReN3 names no individual integration and publishes no connector catalog, connector count, marketplace or integrations page. The eleven partners under In Partnership With are Red Hat, Dell, NTT, AWS, Microsoft, Lenovo, Nutanix, Google, Alibaba, Cisco and Capgemini. They are infrastructure, hardware and systems integrator channel partners, not applications that agents call as tools. ReN3 describes no agent calling tools in external systems during a run. The agents' actions are retrieval, analysis, generation and reporting over the knowledge layer. Sourceren3.ai product page and homepageread 2026-09-01 |
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| Workflow Orchestration | Partial |
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Business users create AI agents with no code tools to automate repetitive work, generate reports, review documents, summarize information and execute enterprise workflows. Each agent does multi step work. An agentic workflow builder that would chain agents into multi step auditable processes is on the roadmap, and it is one of the uses ReN3 names for its seed proceeds. ReN3 names no branching, conditional, looping or parallel steps, no multi agent coordination and no visual flow surface. What ReN3 calls Adaptive AI orchestration is routing requests across models. Sourceren3.ai/product.phpread 2026-09-01 |
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| Knowledge Grounding & RAG | Full |
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A unified knowledge layer connects documents, emails, websites, databases, enterprise applications and multiple file formats, and AI can securely understand and retrieve from it. Examples include PDF, spreadsheet, CAD drawing and scanned image files, and more than 80 file formats are supported, including audio and video. Every AI response is grounded in enterprise knowledge, with citation backed accuracy and comprehensive audit trails. The platform is built on an enterprise content management core, with access rights synced from source systems. ReN3 names no chunking strategy, embedding model, index refresh behavior or retrieval configuration. Sourceren3.ai product page and homepageread 2026-09-01 |
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| Human Oversight & Guardrails | Full |
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Every workspace, AI agent, user and connected data source is governed through centralized policies, role based permissions, approval workflows and comprehensive audit trails. Approval workflows are one of these four governance mechanisms and apply across all agents. Governance and multi tier access controls are built into every AI interaction, and the platform offers explainable agent execution alongside real time AI cost monitoring. ReN3 does not say where an approval sits within an agent run, who is assigned, what happens on rejection or whether the gate is configurable per agent. Sourceren3.ai product page and homepageread 2026-09-01 |
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| Security, Identity & Governance | Partial |
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Alongside IMDA accreditation and a Meta Business Partner badge, ReN3 displays a SOC2-Compliant badge under Accredited By. It publishes no certification type, scope, auditing firm, report or trust center. Governance and multi tier access controls are built into every AI interaction. Comprehensive audit trails come with citation backed accuracy grounded in enterprise knowledge. Sourceren3.ai homepage and footerread 2026-09-01 |
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| Observability & Auditability | Full |
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Organizations keep complete operational visibility, from explainable agent execution to real time AI cost monitoring. That visibility sits alongside governance of every workspace, AI agent, user and connected data source through centralized policies, role based permissions, approval workflows and comprehensive audit trails. Observability is one of the platform's properties at scale, alongside adaptive routing and budget governance. Comprehensive audit trails come with citation backed accuracy grounded in enterprise knowledge, so answers can be checked against their source. ReN3 publishes no retention period, export path, SIEM integration or example trace, and shows no example of how it explains an execution. Sourceren3.ai product page and homepageread 2026-09-01 |
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| Memory & State Persistence | Not documented |
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Knowledge versioning and auto retention are content management features of the platform. ReN3 names no memory or state that persists for its agents. Sourceren3.ai/product.phpread 2026-09-01 |
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| Deployment & Data Residency | Full |
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Pricing is structured by deployment, with three models. Bring Your Own Cloud (BYOC) is deployed in the customer's own cloud. Managed Private Cloud is private tenancy on ReN3 cloud. On-Premise is deployed on onsite or air gapped servers, and ReN3 calls it fully 100% airgapped. All three carry full features. LLM hosting is GPU or API based under BYOC and GPU based under On-Premise, so inference runs on customer infrastructure in the air gapped setup. Deployment targets are public cloud, private cloud, sovereign, on premise and air gapped. Every option is customer controlled or private tenancy, and there is no shared multi tenant offering. Licensing is an annual subscription with concurrent user licensing per site across all three models. Sourceren3.ai plans and product pagesread 2026-09-01 |
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| Prebuilt Agents / Templates / Packs | Not documented |
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An upcoming agent marketplace is on the roadmap, alongside the agentic workflow builder, and both are among the uses of ReN3's funding proceeds. What ships today is a no code builder for deep vertical agents across administration, legal, finance, procurement and HR, built around customers making their own agents in house instead of adopting supplied ones. ReN3 names no template library, agent gallery or prebuilt agent set. Sourceren3.ai/product.phpread 2026-09-01 |
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| Triggers & Channel Coverage | Not documented |
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No event trigger or channel for starting an agent is published. Sourceren3.ai/product.phpread 2026-09-01 |
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| Model Flexibility & Routing | Partial |
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The platform orchestrates multiple AI models and routes each request automatically by reasoning complexity, latency, enterprise policy and token cost, without manual intervention. Automatic provider failover keeps it available regardless of external dependencies. Enterprise policy is one of the four routing inputs, so an organization shapes the routing without choosing a model for each request. Locally hosted models, including Llama, Mistral and Deepseek, run entirely within customer infrastructure in an air gapped deployment. ReN3 reports a 67 percent reduction in token spend and presents intelligent model routing as a way to optimize cost. It names no way to choose a model per task or per agent. Sourceren3.ai product page and homepageread 2026-09-01 |
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| APIs / SDKs / MCP Extensibility | Not documented |
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ReN3 names no public API, SDK, MCP server or webhook, and links no developer documentation or documentation subdomain. The API option for LLM hosting under Bring Your Own Cloud is the platform calling out to a model endpoint. Every way to start is a demo request or contact form, and there is no self serve tier. Sourceren3.ai homepage, product page, plans page, navigation and footerread 2026-09-01 |
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| Testing, Debugging & Optimization | Not documented |
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Accuracy techniques, including cross model verification, run inside the platform. ReN3 names no testing or evaluation tools for customers to use. Sourceren3.ai/product.phpread 2026-09-01 |
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| Browser / Computer-use | Not documented |
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ReN3 names no browser or computer use by its agents. Sourceren3.ai/product.phpread 2026-09-01 |
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The Agentic Index coverage score grades every vendor Full, Partial or Not documented 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.
- Moterra7.0 / 14Adds documented Prebuilt Agents, Templates & Packs and APIs, SDKs & MCP Extensibility
- Khoj7.5 / 14Adds documented Memory & State Persistence and Triggers & Channel Coverage, among others
- Play9.0 / 14Adds documented Memory & State Persistence and Prebuilt Agents, Templates & Packs, among others
- Tektonic AI10.0 / 14Adds documented Prebuilt Agents, Templates & Packs and Triggers & Channel Coverage, among others
- Altilia10.5 / 14Adds documented Prebuilt Agents, Templates & Packs and Triggers & Channel Coverage, among others
- Superblocks10.5 / 14Adds documented Memory & State Persistence and Prebuilt Agents, Templates & Packs, 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