§ 01 — ENTERPRISE SAAS PRODUCT rev: 2026.2

Enterprise Conversations — Private, Intelligent, Secure

Deploy localized conversational agent interfaces running over your proprietary enterprise databases and operational document logs. Maintain absolute cryptographic data confidentiality, enforce department token rate budgets, and eliminate commercial training leaks.

§ 02 — OPERATIONAL PROVENANCE & ORIGIN

Born From Our Own Production Requirements

At DBERT Labs, we enforce a strict engineering standard: we build and operate our tools internally before commercializing them. DBERT Chat was originally engineered to replace insecure public LLM wrappers across our technical training venture studio, where hundreds of engineering fellows interact daily with internal codebase repositories, proprietary legal term-sheet archives, and MSME evaluation reports.

The Engineering Motivation

Off-the-shelf commercial APIs exposed our proprietary venture studio client data to external third-party telemetry and incurred unpredictable token escalation billing during heavy code generation sprints. We constructed DBERT Chat as a hardened, localized retrieval gateway leveraging PostgreSQL pgvector distance indexes and Server-Sent Events (SSE). Today, this identical battle-tested architecture empowers external enterprises requiring air-gapped conversational intelligence.

§ 03 — ARCHITECTURAL INTEGRATION COMMAND

Developer API Gateway Command

Integrate DBERT Chat into existing corporate portals, ERP software, or backend microservices in minutes via standard REST and streaming endpoints.

curl -X POST "https://api.dbert.online/v1/chat" \
  -H "Authorization: Bearer YOUR_ENTERPRISE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "dbert-chat-v2-quantized",
    "messages": [{"role": "user", "content": "Query internal audit logs for Q4 expenditure"}],
    "vector_collection": "finance_records_2026",
    "stream_tokens": true,
    "enforce_privacy": true
  }'
§ 04 — CORE ARCHITECTURAL SPECIFICATIONS

Engineered for Enterprise Throughput & Reliability

1. RAG Vector Storage Engine

Query corporate document repositories, institutional databases, and historical transaction logs utilizing high-throughput PostgreSQL pgvector distance indexing parameters.

  • • Sub-100ms cosine similarity vector matching
  • • Recursive character & semantic overlapping chunking
  • • Native PostgreSQL pgvector schema normalization

2. Token Budgeting & Governors

Define explicit departmental usage quotas and token consumption thresholds to eliminate server overload and enforce rigorous monthly computing cost boundaries.

  • • Configurable seat-level input/output token caps
  • • Distributed bilateral rate-limiting & FIFO queues
  • • Real-time GPU runtime throughput analytical logs

3. Interactive Console UI & SSE

Deliver zero-latency responsive operator interfaces supporting secure real-time Server-Sent Events (SSE) streaming without websocket disconnect overhead.

  • • Asynchronous SSE real-time token streaming pathways
  • • AES-256 encrypted relational session storage tables
  • • Responsive Next.js 16 modular console layouts
§ 05 — SECURITY & COMPLIANCE RIGOR

Enterprise Security & Data Isolation

Designed for regulated Indian operating environments, DBERT Chat implements strict zero-trust boundaries, eliminating data exfiltration risks common in cloud consumer generative chatbots.

Zero Token Training Leaks

We contractually and technically enforce that zero incoming operational prompts, document payloads, or generated completion summaries are ever routed to model training clusters or third-party behavioral aggregation algorithms.

Role-Based Access Control (RBAC)

Integrate directly with enterprise Single Sign-On (SSO) and LDAP identity providers. Enforce strict collection-level read and write permissions ensuring interns and executives only retrieve documentation commensurate with their security clearance.

§ 06 — SYSTEM & DATABASE INTEGRATIONS

Supported Enterprise Ecosystem Integrations

PostgreSQL pgvectorNext.js App RouterOllama RunTimevLLM EngineDocker / KubernetesPrisma ORMAWS / GCP / AzureRedis CacheREST / Webhooks
§ 07 — COMMERCIAL LICENSING & DEPLOYMENT TIERS

Transparent Enterprise SaaS Licensing

Select between managed high-availability cloud deployments or fully offline on-premise container licensing tailored to your Indian organization's governance and computing scale.

Startup Managed Cloud
₹45,000 / month

Hosted inside dedicated Indian region VPCs with automated backups and 50 team seat licenses.

  • Up to 500,000 document embedding queries/mo
  • Managed PostgreSQL pgvector cluster
  • Standard business hour engineering SLA
Select Startup Tier →
Popular Choice
Enterprise Air-Gapped
₹1,20,000 / month

Deployed directly to your corporate bare-metal servers or secure local cloud hardware with zero telemetry.

  • Unlimited local inference & embedding volume
  • Ollama & vLLM open-weights optimization
  • 24/7 dedicated engineering practice support
Inquire Enterprise Tier →
Venture Studio Custom
Custom Scope

Tailored multi-agent operational orchestration and custom domain fine-tuning for specialized industrial workflows.

  • Custom model fine-tuning on domain corpora
  • Full source-code adapter access & training
  • Co-development engineering apprenticeship squads
Discuss Custom Scope →
§ 08 — PRODUCT TECHNICAL KNOWLEDGE BASE

Frequently Asked Questions

DBERT Chat operates entirely within your private containerized environment or isolated cloud virtual private cloud (VPC). Zero customer prompt queries or database completions are transmitted to public commercial aggregators (such as OpenAI or Anthropic public training pipelines). Your sensitive enterprise know-how remains cryptographically bounded within your domain.

Our embedding pipelines support configurable context windows extending up to 128,000 tokens per single interactive thread, utilizing hybrid recursive character chunk partitioning and re-ranking algorithms in PostgreSQL pgvector to retrieve semantic matches with sub-100ms latency.

Yes. For Indian enterprises operating under strict data localization and compliance governance (including defense, fintech, and biomedical sectors), we distribute Dockerized runtime bundles pre-configured for localized weights serving via Ollama and vLLM on enterprise NVIDIA GPU hardware.

The messaging gateway implements distributed Redis token buckets and dynamic queues, capping user requests and output token budgets per department or individual seat. This eliminates server memory exhaustion and maintains predictable operational computational costs.

Enterprise subscription tiers receive dedicated Slack/WhatsApp support channels, custom SQL database adapter integration assistance from our venture studio engineers, and a backed 99.9% uptime Service Level Agreement for managed cloud deployments.

§ 09 — RELATED AI SOLUTIONS & INFRASTRUCTURE

Explore Complementary DBERT Platforms

Document AI Extraction

Convert messy corporate PDFs, scanned invoices, and forms directly into structured JSON schemas.

View Document AI →

Private LLM Hosting

Review transparent hardware architecture and bare-metal server infrastructure in Indian datacenters.

View Private Hosting →

Hiring Automation Suite

Audit candidate codebases, run resume scoring pipelines, and streamline technical recruiting.

View Hiring Suite →
§ 10 — SCHEDULE ENTERPRISE DEPLOYMENT

Custom Enterprise Pricing

Deployed privately to your AWS/GCP VPC. Pricing scales with token volume and active users. Fill out the form below to request a tailored quote and live demo.

Are you an early-stage founder? Incubated startups receive free tier access to this product. Apply for Incubation →

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See how DBERT Chat can streamline your workflows.

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