Enterprise AI Agent Platform
OpenClawby Codenovai
Private AI agent platform for enterprise operations — multi-agent orchestration, complex RAG pipelines, and a fully operational management dashboard. Deployed entirely on your infrastructure.
Platform
Agent Engine
LangGraph-orchestrated multi-agent system. Supervisor pattern coordinates specialist agents for retrieval, reasoning, tool use, and synthesis. Full state machine control flow.
RAG Pipeline
Multi-source knowledge ingestion with hybrid semantic + keyword search. Namespace isolation, citation tracking, and sub-100ms retrieval on millions of chunks.
Ops Dashboard
Fully operational management interface — live agent monitoring, query analytics, knowledge base management, pipeline run history, access control, and alerting.
Agent Architecture
Agents that reason, not just retrieve.
OpenClaw agents operate as stateful reasoning systems — not simple chatbots. Every agent run is orchestrated through a LangGraph state machine, with deterministic control flow, tool selection, error recovery, and full execution tracing.
Orchestration
Multi-Agent Architecture
A supervisor agent coordinates specialist agents — each tuned for a specific task type: retrieval, reasoning, synthesis, code execution, and API calls. LangGraph state machines ensure deterministic control flow.
Reasoning
Adaptive Tool Use
Agents select the right tool at runtime — document retrieval, web search, code interpreter, API calls, or human escalation. Tool selection logic is auditable and configurable per deployment.
Memory
Persistent Agent Memory
Short-term context window management plus long-term memory via vector store — agents recall prior sessions, user preferences, and domain knowledge accumulated over time.
Supported Models
RAG Pipeline
Knowledge at enterprise depth.
The OpenClaw RAG system is built for the complexity of real enterprise knowledge — unstructured documents, structured databases, access controls, and thousands of source files — with the retrieval precision and citation auditability that regulated environments demand.
Multi-Source Ingestion
Ingest from PDFs, DOCX, XLSX, CSV, URLs, APIs, S3 buckets, SharePoint, and SQL databases. Incremental updates keep the knowledge base current without full re-indexing.
Hybrid Search
Combine dense semantic search (OpenAI embeddings) with sparse BM25 keyword search. Reciprocal rank fusion delivers higher precision than either method alone.
Citation Tracking
Every answer is traced back to its source documents with page references, chunk IDs, and confidence scores — full auditability for compliance and validation.
Access-Controlled Namespaces
Partition your knowledge base into isolated namespaces — department-level, project-level, or clearance-level access. Users only retrieve what they're authorised to see.
Chunking Strategies
Semantic chunking, sentence-window chunking, and hierarchical document trees — configurable per document type to maximise retrieval quality.
Sub-100ms Retrieval
Optimised vector index with HNSW algorithm delivers sub-100ms p95 retrieval latency even on knowledge bases with millions of chunks.
Ingestion Sources
Operations Dashboard
Full operational visibility. One interface.
The OpenClaw dashboard gives your operations and engineering teams complete control over every layer of the platform — from live agent sessions and retrieval quality to access policies and token spend. No black boxes.
Live Agent Monitor
Real-time view of every active agent session — current tool, reasoning step, latency, and token consumption. Drill into any run for a full step-by-step trace.
Query Analytics
Latency distributions, query volume trends, top retrieved documents, unanswered queries, and user satisfaction signals — full observability into RAG performance.
Knowledge Base Manager
Upload, index, delete, and version-control documents directly from the dashboard. See indexing status, chunk counts, and last-updated timestamps per document.
Pipeline Run History
Complete audit log of every automation pipeline run — trigger event, steps executed, tools called, errors encountered, and final output.
Access Management
Role-based access control with SSO/LDAP integration. Manage teams, namespaces, API key scopes, and permission policies from a single interface.
API Key Management
Issue, rotate, and revoke API keys per integration. Set rate limits, expiry windows, and scope restrictions. Every key usage is logged and attributable.
Alerting & Incidents
Configurable alerts on error rate thresholds, latency spikes, retrieval quality drops, and pipeline failures. Webhook-based delivery to Slack, PagerDuty, or email.
Token & Cost Analytics
Track token consumption by model, user, team, and use case. Cost attribution across LLM providers with projected spend forecasting.
< 100ms
p95 retrieval latency
∞
Knowledge base size
100%
Query auditability
Zero
Vendor lock-in
Deployment
Your infrastructure. Your data.
Three deployment paths, all sharing the same platform architecture. Choose based on your sovereignty requirements, hardware preferences, and operational complexity tolerance.
Private Cloud
RecommendedDeployed in your AWS VPC, Azure Private Cloud, or GCP VPC — fully isolated from the public internet. Data sovereignty within your cloud account.
Models
OpenAI API + Claude API (data stays in your account)
Timeline
2–3 weeks
Investment
From AED 18,000 setup
On-Premise
Maximum SovereigntyFull air-gapped deployment on your own hardware. Local LLM inference with Ollama — no external API calls. Ideal for regulated industries and sensitive data.
Models
Llama 3.3 70B · Qwen2.5 72B · Mistral · Custom fine-tuned
Timeline
3–5 weeks
Investment
From AED 45,000 (hardware + deployment)
Hybrid
Enterprise FlexibilityCombine local inference for sensitive queries with cloud LLMs for general reasoning. Route queries based on data classification policy — configured at the router level.
Models
Ollama (local) + OpenAI/Claude API (cloud) — policy-routed
Timeline
4–6 weeks
Investment
From AED 35,000
Use Cases
Financial Services
Enterprise Knowledge Assistant
Deploy an AI assistant that answers questions across 10,000+ internal documents — policies, procedures, product specs, and compliance guidelines — with source citations.
Legal & Compliance
Legal Intelligence Platform
RAG system ingesting case law, contracts, regulatory documents, and internal matter files. AI agents draft summaries, flag risk clauses, and surface precedent.
Banking & Wealth Management
Client Onboarding Agent
Multi-agent pipeline orchestrating KYC document extraction, risk profiling, compliance checks, and CRM data entry — automated end-to-end in under 8 minutes.
Enterprise SaaS
Technical Support AI
First-tier support agent with access to documentation, known issues, and customer context. Resolves 70% of tickets without human intervention; escalates with full context.
Technology Stack
Agent Framework
LangGraph
Custom Tool Registry
ReAct + CoT
Agent Evaluations
LLM Layer
OpenAI GPT-4o
Claude 3.5 / 4
Ollama (local)
Custom fine-tuned
RAG & Storage
pgvector (PostgreSQL)
Pinecone
Hybrid BM25 + Dense
S3 Document Store
Infrastructure
AWS ECS / EKS
Next.js Dashboard
Prometheus + Grafana
SST v4 / Terraform
Frequently Asked Questions
Everything you need to know about OpenClaw before the architecture session.
OpenClaw supports any OpenAI-compatible API: OpenAI GPT-4o, Claude 3.5/4 via Anthropic API, and local models via Ollama (Llama 3.3 70B, Qwen2.5 72B, Mistral, custom fine-tuned). In hybrid deployments, query routing determines which model handles each request.
OpenClaw is delivered as a private deployment — either in your cloud account (AWS VPC, Azure) or on your own hardware. You own the infrastructure, data, and deployment. There is no multi-tenant SaaS model. Your data is never commingled with any other organisation.
Incremental ingestion pipelines run on configurable schedules or triggered by webhook events (new document upload, CMS change, database update). Only changed chunks are re-embedded, keeping the index fresh without full re-indexing costs.
The OpenClaw dashboard is a Next.js application deployed alongside the platform. It connects to the same PostgreSQL database that stores agent sessions, pipeline logs, and knowledge base metadata. No additional infrastructure is required.
Yes. The platform includes a REST API and webhook event system. Pre-built connectors exist for ZOHO, HubSpot, Salesforce, and standard REST/GraphQL APIs. Custom integrations are scoped during the implementation phase.
Private cloud deployments typically go live in 2–3 weeks. On-premise deployments, including hardware procurement and setup, take 3–5 weeks. The timeline includes infrastructure provisioning, knowledge base ingestion, agent configuration, dashboard setup, and team onboarding.
All deployments include 90 days of post-launch support: bug fixes, model updates, ingestion pipeline maintenance, and performance optimisation. Extended support contracts cover SLA-backed response times, quarterly performance reviews, and platform upgrades.
Private Demo
See OpenClaw running in your environment.
We run a confidential architecture session — understand your data flows, sovereignty requirements, and knowledge base structure — then demonstrate OpenClaw with your actual document types.
Confidential — NDA signed before any briefing
Architecture designed for your infrastructure
Live demo with your document types (sample data)
Deployment timeline and investment scoped in session
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