Your Data.
Your Agents.
Your AI Edge.
DeepRoot transforms siloed enterprise data into high-impact GenAI outcomes
Why Most GenAI Projects Fail
Industry-leading research reveals the transformative impact of proper data readiness on business performance
of AI projects stall or underdeliver due to poor data quality and governance
Source: Gartner
of executives cite fragmented data as the top barrier to scaling AI
Source: IBM
of data teams spend more time preparing data than building models
Source: McKinsey
Data Readiness Index (DRI)
Measure Exactly How Ready Your Data Is for GenAI
The Data Readiness Index (DRI) provides a quantified, confidence-based view of your enterprise data's AI fitness. By scoring your data across multiple technical and business dimensions, DRI helps you understand where to act — and what's possible today.
Capabilities:
- Audits data quality, governance, structure, bias, and AI alignment
- Produces readiness scores across systems, functions, and datasets
- Identifies causes of low readiness — like incomplete metadata or schema mismatches
- Creates readiness heatmaps for every department and workflow
- Enables benchmarking with historical score tracking to guide improvements
D.A.V.E. (Assistant + Search)
Interact with Your Data Through an AI Virtual Expert
D.A.V.E. (DeepRoot AI Virtual Expert) is your context-aware, natural language interface to DeepRoot. Unlike generic chatbots, it understands your org's structures, roles, and goals — delivering tailored answers and insights directly from your data.
Capabilities:
- Translates conversational prompts into queries, insights, and workflows
- Surfaces bottlenecks, gaps, and performance breakdowns automatically
- Retrieves insights from structured and unstructured data sources
- Generates context-aware, business-aligned responses without requiring technical input
- Collaborates with agents to recommend new automation or GenAI opportunities
Agentic AI
Power Automation with Modular, Intelligent Agents
DeepRoot's Agentic AI layer uses specialized agents to analyze, reason, and act on your enterprise data. These agents work together to transform manual, repetitive tasks into streamlined, AI-driven processes.
Capabilities:
- Automates multi-step tasks through domain-specific agents
- Continuously evaluates metadata, usage patterns, and workflows for optimization
- Classifies and analyzes data for tasks like smart form processing and claims triage
- Proposes new high-value AI augmentations based on historical patterns
- Enables agent-based orchestration of GenAI workflows, from discovery to execution
AI Compass
Find the GenAI Opportunities Your Data Can Actually Support
AI Compass is your discovery engine for turning enterprise data into actionable GenAI strategies. It aligns real-world data conditions with potential AI initiatives — so you don't waste time on pilots doomed to fail.
Capabilities:
- Scans enterprise systems to uncover high-ROI GenAI opportunities
- Evaluates feasibility of use cases based on actual data quality and readiness
- Prioritizes initiatives by potential impact and effort required
- Detects patterns, redundancies, and bottlenecks across your data landscape
- Continuously aligns surfaced use cases with your business goals and priorities
You Imagine It, We Deploy It
Real-world GenAI solutions deployed and running on DeepRoot — transforming businesses across Healthcare, Education, Finance, and more.
Built for Enterprise Confidence
Privacy-First. Deployment Flexible. Audit-Ready.
Data Privacy
Your data stays private; never worry about LLM data leak.
Visibility with xAI
Gain full visibility into AI decisions with detailed logs and memory graphs.
Built-in Guardrails
AI guardrails are safeguards for responsible AI development and deployment.
Open Architecture
A2A, & MCP compliant, Future-ready, agentic architecture built for tomorrow's technology.
Flexible Deployment
Deploy on OCI, AWS, GCP, or on-premise infrastructure.
Enterprise Security
Features like RBAC and encryption secure data at rest and in transit.
Frequently Asked Questions
Get answers to common questions about DeepRoot DataLLM
DeepRoot is a modular Data LLM orchestration platform that connects to structured, unstructured, and semi-structured enterprise data sources and prepares them for GenAI use cases. It performs data profiling, semantic vectorization, and metadata extraction, then activates intelligent agents (task-specific or conversational) that operate within your infrastructure — cloud or on-premise.
Its agentic framework supports use cases like enterprise search, document automation, and domain-specific AI copilots while maintaining full control over your data and models.
DeepRoot runs an automated assessment using its Data Readiness Index (DRI) — a multi-dimensional scoring engine that quantifies your data's AI suitability across seven categories:
- Quality (e.g., completeness, duplication, timeliness)
- Understandability (metadata, provenance, UI clarity)
- Structural Integrity (schemas, formats, access latency)
- Value Metrics (labeling, feature impact, uncertainty)
- Fairness & Bias (class imbalance, discrimination risk)
- Governance (collection, security, privacy, usage control)
- AI Fitness (robustness, explainability, alignment to model constraints)
The DRI output includes numeric scores and diagnostic insights per domain, helping teams de-risk GenAI deployments and prioritize use cases based on feasibility.
Yes. DeepRoot supports model-agnostic orchestration, allowing integration with both public LLM APIs (OpenAI, Claude, Gemini) and private/on-prem models (Mistral, Llama, Falcon, etc.).
Deployment can be hybrid, cloud-native, or edge-based — including support for running models on platforms like NVIDIA DIGITS for GPU-based on-prem inference. DeepRoot automatically adapts routing and agent behavior based on model capabilities and context.
DeepRoot supports a broad range of enterprise-grade use cases through its agentic AI framework:
- Document intelligence: classification, summarization, entity extraction, and workflow routing
- Conversational copilots: internal knowledge access, multi-system querying, and reasoning
- Decision automation: smart form handling, policy checks, confidence-based triage
- Search + synthesis: semantic search across CRMs, file systems, emails, and structured databases
Each use case is evaluated by DeepRoot's AI Compass tool, which scores it across feasibility, impact, and data readiness — helping teams avoid overambitious or underperforming pilots.
With prebuilt connectors, secure metadata-based ingestion, and agent templates, most clients can deploy their first DeepRoot use case in 2–4 weeks. Onboarding includes:
- Initial DRI assessment
- Source system integration (no data movement, vector-based)
- LLM orchestration layer setup
- Agent design + testing
- Audit and compliance checks
DeepRoot also supports RBAC, data masking, and on-prem model hosting, allowing deployment in high-security or regulated environments (healthcare, BFSI, education, etc.).
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Copyright | Innoflexion | 2024