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AI & GenAI Enablement on Data Platforms

Saama engineers production-grade AI on your existing data platforms. We deliver Talk-to-Data, RAG, and Agentic AI grounded in governed enterprise data, ensuring accuracy over generic LLM outputs.

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THE CHALLENGE

Bridging the Gap Between AI Pilots and Trusted Scale

Analysts often wait days for queries that should be conversational. Vast unstructured data—contracts, PDFs, and emails—remains untapped, hiding critical business intelligence from analytics teams.Drifting KPI definitions and LLM hallucinations often cause GenAI pilots to fail in production. This leads to increased compute spend, security risks, and unverified outputs, creating a gap between AI ambition and enterprise capability.

How Saama Helps

Grounded, Sovereign Enterprise Intelligence.

We replace unverified model outputs with AI architectures integrated into your modern data platform. Using Knowledge-Augmented RAG and orchestrated agent workflows, Saama ensures AI is grounded in corporate logic and strictly governed.

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Solutions for the Modern Data Infrastructure Lifecycle

Pillar 1 — Talk-to-Data & Conversational AI

Replacing static dashboards with secure, conversation-driven access to complex enterprise data assets.

Agents
Conversational Interface Agent, Semantic Model Codifier
Grounded Frameworks
Tailored analytics interfaces built on Snowflake Cortex, Databricks Genie, or Saama AI stacks using the Conversational Interface Agent.
Semantic Design
Using the Semantic Model Codifier to transform domain models into YAML structures, providing an immutable grounding layer.
Embedded Surfaces
Injecting AI capabilities into productivity hubs like Microsoft Teams, Slack, and Streamlit.

Saama Llama Impact

↓ 70% Reduction in Ad-Hoc Report Generation Requests | 100% Alignment on Conversational Metric Definitions

Pillar 2 — RAG, KRAG & Enterprise Search

Turning dark, unstructured enterprise content into queryable, first-class citizens of your analytics estate.

Agents
Hybrid Retrieval Orchestrator, Domain Fine-Tuning Agent
Citation-Traced RAG
Search infrastructure across contracts and emails to turn unstructured text into verified intelligence.
Knowledge-Augmented RAG (KRAG)
Managed by the Hybrid Retrieval Orchestrator to combine content blocks with relational databases for contextual accuracy.
Domain Fine-Tuning
Tuning models on industry terminology and internal logic to replace generic LLM defaults.

Saama Llama Impact

↑ 85% Efficiency Gains in Unstructured Document Audits | Near-Zero Hallucination Rates in Domain Queries

Pillar 3 — Agentic AI Workflows

Moving operations from single-prompt interactions to orchestrated, autonomous multi-step agent networks.

Agents
Goal-Directed Task Orchestrator, Traceability & Governance Sentinel
Chain Reasoning
Goal-Directed Task Orchestrator links complex logic and automated tool execution for autonomous task completion.
Governance Sentinel
Rigid authorization checkpoints and auditability ensure AI outputs safely amplify human expertise.
Agentic Blueprints
Deploying reusable, use-case-specific agent blocks on a shared framework to accelerate deployment.

Saama Llama Impact

Weeks from Ideation to Production for Novel Agents | 100% Audit Traceability for Agent Actions

How Saama Powers Your MDP Success

Strategic Infrastructure Benefits

1

Accelerated Innovation

Move from pilots to stable, high-performance models using secure data grounding layers.

2

Cognitive Persistence

Scale institutional logic through networks that preserve operational memory and execute complex tasks.

3

Capital Protection

Reduce LLM spending with token-efficient architectures leveraging your existing platform assets.

Ready to move from AI demos to grounded production?

Modern Enterprise AI is about grounded, governed capability engineered directly into the data platforms you already own.

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