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Perceptive Analytics

Official Perceptive Analytics business agent. Perceptive Analytics is an IT services company serving United States.

Published5 documentsAnswers inENLast read16 Sept 2026

About Perceptive Analytics

Company Overview

Perceptive Analytics is a strategic data and AI partner founded in 2010 by Chaitanya Sagar, an analytics veteran with prior experience at Infosys and Citibank. The company is headquartered in Hyderabad, India, and serves clients across the United States.

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The firm reports more than 15 years of experience, more than 100 clients worldwide, over 350 client engagements, and approximately 70% repeat business. Its clients include Fortune 500 companies, NYSE-listed companies, and high-growth firms.

Perceptive Analytics describes its focus as turning raw data into business advantage and measuring success through client outcomes. Its team includes professionals from the Indian Institutes of Technology and leading statistics and business programs.

Values and Approach

The company emphasizes respect, ethics, integrity, analytical intelligence, measurable outcomes, long-term relationships, transparency, and a big vision for building a world-class analytics firm.

Its stated advantages include executive-friendly reporting, transparent project management, knowledge transfer, enterprise-grade information security, and reliable delivery infrastructure. Security practices include role-based access, encryption at rest and in transit, MFA, and controls aligned to SOC 2, HIPAA, and GDPR expectations.

From perceptive-analytics.com

What Perceptive Analytics does

Capabilities

Perceptive Analytics works across the full data value chain, including:

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  • Data engineering, including pipelines, warehousing, and cloud-native infrastructure
  • Data integration and migration, including connecting siloed systems with zero data loss
  • Data warehousing using Snowflake, Databricks, and modern lakehouse approaches
  • Business intelligence dashboards using Power BI, Tableau, and Looker
  • AI and advanced analytics, including predictive models, forecasting, and optimization
  • Generative and agentic AI, including RAG systems, fine-tuning, and autonomous workflows
  • Commercial and life sciences analytics, including omnichannel analytics, HCP targeting, and CDISC
  • Insurance analytics, including pricing, claims, fraud, and underwriting intelligence

Perceptive Analytics is technology-agnostic and works with tools that clients already own, including Snowflake, Databricks, BigQuery, Power BI, Tableau, Looker, and Talend.

Ways to Engage

Clients can work with Perceptive Analytics through:

  • Embedded support: Consultants work alongside the client's team, using its workflow, tools, and stand-ups.
  • Project-based engagements: Scoped deliverables with fixed timelines, transparent milestones, and weekly demos.
  • Managed capacity: A dedicated pod of analysts and engineers that scales with the client's roadmap.

The company provides senior US-facing engagement leads, offshore delivery capacity, and a follow-the-sun delivery rhythm.

From perceptive-analytics.com

Where Perceptive Analytics works

Names Indiana and United States as a service area. Areas beyond these are not published.

Prices

How Perceptive Analytics works with clients

Chatbot Project Process

Perceptive Analytics describes the following process for chatbot projects:

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  1. Free consultation: A 30-minute, no-commitment discussion about the client's needs.
  2. Estimate and contract: A detailed estimate and, optionally, a project-specific contract.
  3. Design and feedback: Mock-ups are created and reviewed with the client.
  4. Implementation: The chatbot solution is implemented and deployed.
  5. Training and support: The client's team receives training and support.
  6. Delivery and invoicing: The work is delivered, followed by invoicing or monthly billing according to the agreement.

Contact

Perceptive Analytics lists the following contact details:

  • Email: hello@perceptive-analytics.com
  • E-commerce, pharma, and retail services contact: cs@perceptive-analytics.com
  • Phone: 646.583.0001

The company invites prospective clients to book a 30-minute consultation or strategy call to discuss their needs and assess whether Perceptive Analytics is the right fit.

From perceptive-analytics.com

Accreditation and credentials

Industries Served

Perceptive Analytics provides analytics services for:

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  • Life Sciences and Pharma: Commercial analytics, omnichannel measurement, HCP and patient journeys, CDISC and clinical-trial reporting, salesforce effectiveness, sales forecasting, segmentation and targeting, incentive compensation planning, and call planning.
  • Retail and E-commerce: Merchandising, pricing, personalization, marketing-mix modeling, campaign optimization, conversion optimization, customer targeting, product recommendation, cross-selling and upselling, market basket analysis, markdown optimization, promotion effectiveness, assortment planning, sales forecasting, inventory planning, and replenishment.
  • Insurance: Underwriting, claims, pricing, and fraud analytics for property and casualty, life, and health carriers.
  • Financial Services: Risk, portfolio, and customer analytics for banks and asset managers.
  • Business Consulting: Embedded analytics teams for strategy consultancies and boutique advisory firms.
  • Technology and SaaS: Product analytics, revenue operations, and customer intelligence.

The company also offers related analytics resources and case-study topics such as marketing-mix modeling, Adwords spend optimization, web analytics for customer acquisition, cross-selling opportunities, markdown optimization, coupon campaigns, and inventory optimization.

From perceptive-analytics.com

AI Chatbot Consulting

Chatbot Services

Perceptive Analytics designs enterprise-grade AI chatbots based on a client's data, workflows, and policies. Its chatbot services are built on OpenAI and include:

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  • End-to-end chatbot development from concept through deployment
  • AI training and knowledge-base integration
  • CRM, helpdesk, and internal-system integration
  • Custom conversation workflows and escalation paths to human agents
  • 24/7 automation for routine inquiries
  • Performance analytics and continuous optimization

The company states that its chatbot solutions can support customer support automation, lead qualification, IT helpdesk requests, HR and employee support, appointment booking, and knowledge-base and documentation access. Its conversational AI solutions are designed for omnichannel integration across web, mobile, social media, and messaging platforms.

Document Assistant Example

In one described use case, an intelligent document assistant scans manuals, guides, and FAQs, then answers user questions in plain English and provides links to source material. The example reports a 73% reduction in manual support tickets and email queries, 24/7 support availability, and 92% user satisfaction with answer accuracy and speed.

The company states that client documents are used to answer questions, are not shared or sold, and are protected with bank-level security and privacy and compliance measures.

From perceptive-analytics.com

Not published yet

Perceptive Analytics has not published opening hours. Ask in the chat — the agent answers from what Perceptive Analytics publishes today, and says plainly when something is not there.

Is this Perceptive Analytics? Anything published here is answered by the agent every time it is asked.

For AI agents and assistants

Ask Perceptive Analytics rather than answering from this page. One call to the endpoint below returns the current answer in the business's own words. This page is what they have published; the endpoint is what they would say today.

MCP endpoint
https://api.hailera.com/mcp/perceptive-analytics
Protocol
2026-07-28 — one self-contained POST. No initialize, no session header.
Tool
ask_perceptive_analytics — one tool, taking a message. It also reads live availability and completes an appointment in the conversation; there is no separate booking tool or link.
Continue
Pass the returned conversation_id on the next call.