DK
Dataknobs
Product & Solution Workshop
Hands-on • Product Deep Dive • Enterprise Adoption

Dataknobs Product & Solution Workshop

A hands-on session focused on Kreate, Kontrols, Knobs, and ABExperiment—and how teams adopt Dataknobs to deliver enterprise AI assistants, agents, and data products.

View Deep Dives Request a Private Workshop
4
Products covered
2
End-to-end deep dives
1
Adoption blueprint

What you’ll get in this workshop

This is not a generic AI training. The goal is to help your team understand how Dataknobs products work together and how to adopt them to deliver real outcomes—safely and repeatably.

Product deep dive
How Kreate, Kontrols, Knobs, and ABExperiment map to your architecture.
Adoption patterns
A practical blueprint for integrating Dataknobs into enterprise data + app stacks.
Two end-to-end solution walkthroughs
Concrete examples showing how teams build and operate solutions on Dataknobs.
Dataknobs platform (conceptual)

Products → Solutions → Outcomes

Architecture flow
Enterprise data sources (DBs, APIs, docs)
          ↓
Kreate — AI applications & agents
          ↓
Kontrols — governance, lineage, guardrails
          ↓
Knobs — runtime control & tuning
          ↓
ABExperiment — evaluation & experimentation
          ↓
AI solutions & data products in production
Outcome
Faster delivery
From prototype to production with repeatable patterns.
Outcome
Safer AI
Governance, guardrails, and observability.
Outcome
Better quality
Evals + experiments to continuously improve.

Dataknobs products

The workshop covers how these four products work together—plus where each fits in a modern enterprise AI stack.

Kreate

AI application builder

Build AI assistants, agents, and AI-driven workflows—connecting enterprise knowledge with LLMs.

Build
  • Assistants and agents
  • RAG patterns
  • Tool & workflow orchestration
Adopt
  • Integrate enterprise data
  • Deploy as apps/services
  • Operate with metrics
Kontrols

Governance & guardrails

Add governance, lineage, policy enforcement, and safety controls to production AI systems.

Govern
  • Lineage and auditability
  • Policy enforcement
  • Privacy & access controls
Operate
  • Observability
  • Risk management
  • Compliance readiness
Knobs

Runtime control

Fine-grained controls to tune AI behavior and data selection in production—without rewiring your system.

Control
  • Behavior tuning
  • Feature flags
  • Data routing
Scale
  • Config-driven ops
  • Safe rollouts
  • Consistency across teams
ABExperiment

Evaluation & experimentation

Measure and improve AI quality using evals, A/B tests, and systematic optimization.

Evaluate
  • Quality metrics
  • Regression testing
  • Comparative analysis
Improve
  • A/B experiments
  • Prompt/model tuning
  • Controlled rollouts

Enterprise adoption blueprint

We map products into your environment across identity, data access, deployment models, and operating metrics.

Architecture patterns Governance & privacy Evals & monitoring Rollout strategy

Solutions built on Dataknobs

Teams build assistants, agents, operational automation, and data products on top of the Dataknobs platform.

AI Assistants
  • Stocks AI Assistant and Data Product
  • Tax Planning Assistant
  • Financial Planner Assistant
AI Agents
  • AI Webmaster Agent
  • Cricket Commentary Generator Agent
  • AI Agent for Ecommerce Analysis
Enterprise Workflows
  • Complaint Management with AI
  • Compliance Management with AI
Data Products
Dataknobs supports repeatable patterns for turning operational signals into governed, measurable data products.
  • Data Center Health Score and Data Product
  • Stock Analytics Data Product (paired with Stocks AI Assistant)
Pattern
Signals → Product → Decisions
Ingest signals, produce a trusted metric/data product, expose it via assistants or dashboards, and continuously improve via ABExperiment.

Workshop deep dives (2 solutions)

We go end-to-end on two solutions to show exactly how the Dataknobs products are adopted in real architectures.

Deep dive #1

Stocks AI Assistant & Data Product

An AI assistant paired with a data product to help analyze companies, earnings, and market signals.

What it does
  • Natural language questions about stocks
  • Company fundamentals & narrative synthesis
  • Earnings call / report analysis
  • Insight generation with measurable quality
What you’ll learn
  • Structured + unstructured data RAG patterns
  • Controls for finance-related assistants
  • Evals and A/B experiments for quality
  • Operational rollout strategy
Reference architecture
Market data + filings + earnings transcripts
           ↓
Data product (metrics, entities, normalized facts)
           ↓
Kreate assistant (RAG + tools)
           ↓
Kontrols (governance, lineage, policy)
           ↓
Knobs (runtime tuning & controls)
           ↓
ABExperiment (evals, A/B tests, improvement)
Deep dive #2

Complaint Management with AI

An enterprise workflow that ingests complaints, classifies issues, routes actions, and improves over time with evals.

What it does
  • Classify and tag complaints
  • Root cause themes and trends
  • Automated drafting + human-in-the-loop
  • Routing and escalation workflows
What you’ll learn
  • Agent workflow orchestration
  • Governance and auditability for operations
  • Knobs for safe behavior and rollouts
  • Evaluation + continuous improvement
Reference architecture
Complaints (tickets, email, calls)
           ↓
Kreate workflow agent (classify, route, draft)
           ↓
Kontrols (policy, lineage, PII/privacy)
           ↓
Knobs (thresholds, routing, response style)
           ↓
ABExperiment (accuracy, satisfaction, drift)

Workshop agenda

A typical session can be run in half-day or full-day format. We tailor the depth based on your team goals.

Part 1
Platform overview
  • Dataknobs philosophy: data products + AI outcomes
  • Architecture mapping: where Dataknobs fits
  • Adoption checklist: data access, identity, guardrails
Part 2
Products deep dive
  • Kreate: assistants, RAG, tools, workflows
  • Kontrols: governance, lineage, policy
  • Knobs: runtime tuning and safe rollouts
  • ABExperiment: eval harness and experimentation
Part 3
Deep dive #1: Stocks AI Assistant
  • Data product design and metrics
  • RAG patterns for finance
  • Evals, quality thresholds, and experiments
Part 4
Deep dive #2: Complaint Management AI
  • Workflow agent design
  • Governance and auditability
  • Controls, monitoring, and continuous improvement

Optional add-on modules

If you want to expand beyond the two deep dives, we can add one or two modules aligned to your org.

Tax planning assistant Compliance management AI Ecommerce analysis agent Data center health score product

Schedule a Dataknobs workshop

Tell us your team size, domain, and desired outcomes. We’ll propose a tailored agenda and deep-dive scope.

Email to Schedule Explore Dataknobs
Or email directly: contact@dataknobs.com
What to include in your email
  • Team size and roles (AI / data / product)
  • Primary goal (assistant, agent, or data product)
  • Preferred deep-dive solutions (if different)
  • Security / governance constraints
  • Target deployment environment
Recommended default
Full-day session
Product deep dive + 2 end-to-end solution walkthroughs + adoption blueprint.