DeepQ-AI

What DeepQ-AI does

DeepQ-AI (DEEPQAI BUSINESS SOLUTIONS PRIVATE LIMITED), founded in 2021 and headquartered in Bengaluru, India, operates an agentic AI platform that takes business problems from strategy through solution to deployment. The platform combines a conversational session interface (in Strategy, Solution, and Deployment modes), a full-transparency Inspector layer that exposes every methodological decision, project workspaces for compounding context, an Observatory for organization-wide portfolio visibility, a five-agent execution layer (Director, Strategist, Data, Modeler, Deployer), and an Institutional Memory system that retains domain context, validated decisions, and patterns across sessions. The technology layer integrates multiple third-party LLMs (Anthropic, OpenAI, Google Gemini) with predictive models (gradient-boosted trees, XGBoost, LSTM), NLP pipelines, and graph analytics, deployed across AWS, Microsoft Azure, and Google Cloud in shared, dedicated, or on-premises configurations.

The company sells packaged, verticalized solution bundles across six industries — Banking, Financial Services, Insurance, Healthcare, Retail, and CPG — and three role-targeted offerings (Business Leaders, Business Managers, Functional Experts), supported by a 312+ solution Inspiration Lab, a free Academy learning module, and a free Bootcamp program where real customer problems are solved live. Customers range from mid-market digital lenders ($2-5B loan book) to enterprise organizations, with cited deployments running 46-128 concurrent problems and $148M-$212M YTD value yield per industry (representing customer-side value rather than DeepQ revenue). Pricing is hybrid: a fixed monthly subscription ($2K-$3K/month Team tier; custom Enterprise) plus consumption-based credits consumed as problems move from question to deployed solution, with a Forward Deployed Success Team (Client Partner + AI Engineer) included in every paid engagement. The company is privately held and founder-led by Prashant Dixit (Founder & CEO) and Ratnesh Ranjan (Chief Technology and AI Officer), and reports no external institutional investors in available materials.

Name

DeepQ-AI

Legal name

DEEPQAI BUSINESS SOLUTIONS PRIVATE LIMITED

Website

https://www.deepq-ai.com

Company type

Private

Founded year

2021

Operating status

Operating

Headcount range

11–50 employees

Short description

DeepQ-AI operates an agentic AI platform that takes business problems from strategy through deployment, serving mid-market and enterprise buyers across Banking, Insurance, Healthcare, Retail, CPG, and Financial Services via a subscription plus consumption-based credits model.

Ownership category

akta.pro rank

Product category

Agentic AI Platform

NAICS

Software Publishers (513210), Custom Computer Programming Services (541511)

SIC

Services-Prepackaged Software (7372), Services-Computer Programming, Data Processing, Etc. (7370)

akta.pro primary industry

End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA)

akta.pro secondary industries

AI Integration & Orchestration Platforms (Connectors, Workflow, iPaaS for AI) (HDAEANAI), Enterprise AI Data & Knowledge Platforms (Vector Databases, Knowledge Graphs) (HDAEANAH), Audit, Explainability & Accountability Tooling (traceability, reporting) (HDAAAKAL), Model Serving, Inference & Deployment Platforms (APIs, Edge/On-Prem) (HDAEANAC)

Keywords

• Agentic AI platform
• Enterprise decision intelligence
• Machine learning deployment
• Domain-specific AI solutions
• Business problem solving software

Headquarters

HQ city

Bengaluru

HQ country

India

HQ region

Asia

Offices2 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Infrastructure, Operations, Marketing or Sales

Revenue model

1. Subscription: Fixed monthly subscription providing access to the DeepQ AI platform, methodology, embedded domain knowledge, institutional memory, and platform access. Subscription tiers include Team and Enterprise levels.
2. Credits (Consumption): Credits consumed as problems move from question to deployed solution. Credit consumption varies by problem complexity — Strategy sessions consume less, Solution and Deployment consume more. The economics compound: the tenth problem costs less than the first, the hundredth costs less than the tenth.
3. Free Evaluation: Free signup with business email includes full access to Inspiration Lab and Academy, evaluation credits, and ability to run Strategy and Solution sessions end-to-end. No credit card or sales call required.

Pricing tiers

Go-to-market motion3 records

Distribution channels5 records

Marketing channels8 records

Core offering

DeepQ-AI sells an agentic AI software platform that combines adaptive methodology, five specialized agents, and embedded domain knowledge to take business problems from strategy through solution to deployment. The platform exposes Sessions (Strategy/Solution/Deployment modes), an Inspector transparency layer, Projects workspace organization, an Observatory cross-portfolio dashboard, and an Institutional Memory knowledge base. It is offered with industry-specific context bundles for Banking, Financial Services, Insurance, Healthcare, Retail, and CPG, priced via a subscription plus consumption-based credits model.

Product overview

DeepQ AI is a unified agentic platform for end-to-end business problem-solving with AI — combining six interconnected components in one place: Sessions (conversational problem-solving interface with Strategy/Solution/Deployment modes), Inspector (full methodology transparency and audit trail), Projects (context persistence across related sessions), Observatory (organization-wide visibility across four views), Agents (specialized AI agents executing at machine speed), and Institutional Memory (compounding knowledge that makes each problem faster than the last). The platform is offered alongside role-specific offerings (Business Leaders, Business Managers, Functional Experts) and industry-specific bundles (Banking, Financial Services, Insurance, Healthcare, Retail, CPG), plus learning resources (Inspiration Lab with 312 pre-built solutions, Academy). Engagement is priced via Subscription (fixed access) plus Credits (consumption-based), with a Forward Deployed Success Team included in every paid engagement. The company was founded by Prashant Dixit (Founder & CEO) and Ratnesh Ranjan (Chief Technology and AI Officer), headquartered in Bengaluru, India.

Differentiator

Problem solved

Functional benefit

Brands

• DeepQ AI Platform: Agentic AI platform for end-to-end business problem solving - strategy, solution, and deployment.
• Inspiration Lab
• Academy
• Bootcamp

Products and services

• DeepQ AI Platform Software-as-a-Service agentic AI platform for end-to-end business problem solving that combines adaptive methodology, specialized agents, and embedded domain knowledge across Banking, Insurance, Healthcare, Retail, CPG, and Financial Services to take problems from strategy through solution to deployment.
• DeepQ AI Bootcamp Free working session service in which a DeepQ AI Client Partner and AI Engineer work a real customer business problem live, on the customer's data or representative data, with no sales pitch and no commitment, sized as a virtual 1–1.5 hour session or an in-person 2–3 hour session.
• Forward Deployed Success Team Dedicated Client Partner and AI Engineer service bundled into every paid DeepQ AI engagement, providing strategic scoping support, platform coaching, and solution guidance that tapers as customer teams become self-sufficient.
• Inspiration Lab Pre-built AI solution library offering 312+ real solutions across 10 industries (BFSI, Retail, Healthcare, Insurance, FMCG/CPG, Telecom, Manufacturing, Logistics, Education, Energy) and functions such as AML, credit risk, fraud, claims, pricing, and demand, browsable and runnable on synthetic data for evaluation and adaptation.
• DeepQ AI Academy Free self-paced learning platform that teaches users how to describe business problems, direct sessions, use the Inspector, and build institutional memory across six categories — Getting Started, Working with Sessions, Verifying and Reviewing, Working with Projects, Organizational Scale, and Role-specific paths.

Quantifiable outcome

• Collections propensity improvement: +18% recovery
• +31 more outcomes

Segments10 records

Ideal customer profiles5 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Integration14 records

AI capability10 records

Feature13 records

Partnerships

Nine partnerships are on record, tiered core.

• Microsoft for StartupscoreGTM or Marketing PartnerEcosystem partnership through which DeepQ AI gains marketplace visibility, co-marketing opportunities, and referral pipelines for startup and enterprise customers. Part of Microsoft's initiative to support AI ISVs.
• NVIDIA ConnectcoreGTM or Marketing PartnerNVIDIA Connect Program for advancing ISV innovation. Provides DeepQ AI with technical resources, GPU infrastructure access, co-marketing, and referral pipeline for AI-focused customers.
• AWS ActivatecoreGTM or Marketing PartnerAWS Activate program providing cloud infrastructure credits, technical support, and marketplace visibility for startup and enterprise customers on AWS.
• AnthropiccoreTechnology or IntegrationLLM provider powering DeepQ AI's agentic execution layer. Anthropic's Claude models handle natural language understanding, reasoning, and generation within the platform.
• OpenAIcoreTechnology or IntegrationLLM provider integrated into DeepQ AI's platform alongside Anthropic. Provides GPT model capabilities for specific use cases within the agentic execution layer.
• Google (LLM)coreTechnology or IntegrationLLM provider integrated into DeepQ AI's platform for Gemini model capabilities. Provides additional language model options within the platform's agentic layer.
• AWScoreTechnology or IntegrationPrimary cloud infrastructure provider for DeepQ AI's shared cloud deployments. AWS Activate partner. Handles data storage and processing for most standard engagements.
• Google CloudcoreTechnology or IntegrationCloud infrastructure provider for DeepQ AI deployments. Used alongside AWS and Azure for multi-cloud deployments and regional data residency requirements.
• Microsoft AzurecoreTechnology or IntegrationCloud infrastructure provider for DeepQ AI deployments. Microsoft for Startups partner. Provides Azure-based deployment options for enterprise customers.

Scale indicators7 records

Recent moves6 records

Expansion highlights6 records

Emerging players

• Scale AI: AI data and evaluation platform serving enterprises and government with model fine-tuning and testing infrastructure. Partial overlap in the AI-for-enterprise problem-solving space with a different monetization model (data/eval vs problem-solving platform).
• Quantexa: Decision intelligence platform specializing in AML, fraud detection, KYC, and entity resolution for financial services. Deeply comparable to DeepQ AI's banking and AML offerings with a narrower but overlapping vertical focus.

Direct peers

• DataRobot: Enterprise AI/ML platform providing automated model building, deployment, and monitoring with vertical offerings. Directly comparable in targeting business users with end-to-end AI problem-solving rather than requiring data science expertise.
• C3.ai: Enterprise AI applications platform offering pre-built industry solutions (financial services, manufacturing, healthcare) similar to DeepQ AI's verticalized Inspiration Lab approach.
• H2O.ai: Enterprise AI cloud platform providing automated ML and generative AI capabilities with strong financial services and regulated-industry focus. Comparable platform-level positioning with vertical specialization.
• Palantir Technologies: Enterprise AI platform for end-to-end problem-solving across operations, defense, healthcare, and financial services with deep ontology and audit-ready deployment. Closest analog in combining domain-specific AI workflows with full-stack problem-to-production pipelines.

Broad incumbents

• Databricks: Unified data and AI platform with Mosaic AI for model building, serving, and governance. Overlaps with DeepQ AI's enterprise AI deployment capabilities but as a much broader data-platform incumbent rather than a problem-solving specialist.
• Microsoft (Azure AI / Copilot Studio): Hyperscaler with Azure AI Foundry, Copilot Studio, and Fabric offering multi-agent orchestration and vertical AI templates. Competes with DeepQ AI at the agentic orchestration layer and benefits from bundled procurement and existing enterprise relationships.
• SAS: Established analytics and AI platform with deep vertical offerings in banking, insurance, healthcare, and retail. Competes in the same verticals but with a legacy on-prem-first footprint rather than a cloud-native agentic approach.
• Google (Vertex AI Agents): Hyperscaler offering Vertex AI Agent Engine and Gemini-based agentic capabilities integrated with Google Cloud data services. Competes with DeepQ AI on the underlying agent infrastructure layer with massive distribution advantages.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

• LinkedInlinkedin.com/company/deepq-ai

Compliance12 records

Revenue estimate

Valuation estimate

Number of profiles

Profiles2 records

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about DeepQ-AI