Retrieval-Augmented AI for Enterprise

Automate knowledge access, eliminate research bottlenecks, and turn regulatory complexity into instant answers. Our RAG systems help teams move faster and smarter, without unnecessary overhead.

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RAG-Powered Enterprise AI

We Integrate RAG into Your Systems

We don’t just give you another chatbot — we connect directly to your backend systems and deliver a secure, enterprise-grade chat assistant powered by Retrieval Augmented Generation (RAG). The assistant instantly accesses your content and knowledge bases, giving your team accurate, context-aware answers in real time.

And unlike big-ticket vendors, we do it at a reasonable budget with dedicated support from our team. From first integration to daily use, you’ll have experts on call to make sure your copilot works seamlessly inside your environment.

  • Best in Class Models: Choose from 20+ models, including Claude, ChatGPT, Perplexity, Grok, and Gemini, balancing speed, accuracy, and cost.
  • Security First: Data stays protected. The assistant connects to your systems securely and respects enterprise compliance requirements.
  • Enterprise Ready Workflows: Seamlessly integrate with monday.com, Notion, Google Workspace, HubSpot, and more, so AI works inside the platforms your teams already use.
  • Dedicated Support, Predictable Cost: We help you implement quickly, provide hands-on assistance, and keep budgets transparent so there are no surprises.
RAG-Powered Transformation

From Static Documents to Strategic AI

Multi-Source Retrieval

Multi-Source Retrieval

Pull knowledge across regulatory filings, contracts, policies, and internal wikis to answer complex business questions instantly.

  • Search and reason across PDF, DOCX, Excel, and HTML

  • Index thousands of documents for long context retrieval

  • Ingest and normalize disparate file formats
Domain-Aware Reasoning

Domain-Aware Reasoning

Custom tuned to your sector (finance, pharma, legal). Our systems adapt to the nuances of your vocabulary and regulations.

  • Embed industry glossaries and taxonomies into responses

  • Integrate regulatory schemas and compliance thresholds

  • Handle noisy data from OCR, scanned docs, and legacy files
Real-Time Decision Support

Real-Time Decision Support

Empower analysts, compliance officers, and executives with accurate, sourced answers on demand.

  • Ask natural language questions about deals, trials, or policies

  • Get cited answers linked to document passages

  • Validate reasoning chains and surface contradictions
Enterprise-Ready Orchestration

Enterprise-Ready Orchestration

Scale securely across teams, departments, and regions, compliant from the start.

  • Access controls and content scoping for sensitive data

  • Deploy in your cloud (AWS, Azure, GCP) or on-prem

  • Auditable responses with citations and source links

Frequently Asked Questions

RAG systems combine large language models with vector search over your organization's content. Instead of hallucinating answers, the system pulls evidence directly from your documents to provide grounded, explainable results.

Unlike generic chatbots, we build domain tuned RAG pipelines with secure ingestion, retrieval optimization, and custom prompting to suit enterprise workflows.

Yes. We connect to SharePoint, Confluence, Documentum, custom APIs, or S3 and Google Drive folders—syncing and indexing your content automatically. We also build dedicated integrations that your admins can manage through the Model Context Protocol (MCP) for fine-grained control and governance.

We support both client hosted and fully managed deployments. For regulated environments, we recommend your own VPC or on-prem infrastructure.

Our core clients operate in life sciences, financial services, legal, consulting, and manufacturing, but our architecture is sector agnostic.

No. We support multiple LLMs and can route queries across models to balance accuracy, latency, and cost.

Unlock Your Data

Deploy internal copilots that retrieve, reason, and respond securely across your most sensitive documents.

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