Ship Revenue-Grade GenAIIn Weeks, Not Quarters
We partner with CTOs, Heads of Data, and Ops leaders to prioritize high-impact use cases, build secure pilots, and move winning workflows into production. Clear ROI, strong adoption, and full team handoff.
Engagements Designed to Get Shipped
Pick the support level you need, from strategy sprints to embedded delivery for production rollouts.
AI Opportunity Mapping Sprint
A focused consulting sprint to identify where GenAI will create measurable value first, with clear delivery and ownership plans.
- Stakeholder interviews
- Use-case prioritization matrix
- Data + security readiness review
- 90-day implementation roadmap
GenAI Pilot Build
Design and build a production-minded pilot around one high-value workflow, with evaluation criteria and adoption targets from day one.
- RAG or AI agent implementation
- Evaluation harness and test cases
- Guardrails + human-in-the-loop flows
- Pilot launch with KPI baseline
Productionization & MLOps
Harden your successful pilot for production with observability, governance, and repeatable deployment workflows.
- Prompt/model version control
- Latency + quality monitoring
- Cost and performance tuning
- Runbooks + incident response
AI Workflow Automation
Automate repeatable knowledge work across support, operations, and internal teams using agents and retrieval-based systems.
- Back-office copilots
- Document + inbox triage
- CRM/ERP workflow orchestration
- Escalation-safe automation
Knowledge & Data Foundation
Build the retrieval and data layer your GenAI products depend on, with quality controls and enterprise access boundaries.
- Document ingestion pipelines
- Vector + metadata architecture
- PII handling and access policies
- Source-of-truth data contracts
AI Governance & Enablement
Help your teams adopt AI responsibly with practical governance standards, playbooks, and internal capability building.
- Model risk assessments
- Responsible AI guardrails
- Policy and approval workflows
- Team training + handoff
Stack-Agnostic, Outcome-Driven
We work with your existing cloud and tools when possible, then add only what improves speed, quality, or cost.
LLMs & GenAI
ML Frameworks
Cloud & Infra
Data & Vector DBs
Measurable Outcomes, Not Just Demos
Each project below started with a baseline metric and a delivery plan tied to business value.
Enterprise RAG System for Fortune 500 Insurer
The Challenge
Claims adjusters spending 4+ hours daily searching through policy documents and precedent cases.
Our Solution
Built a multi-modal RAG system with hybrid search (semantic + keyword) over 2M+ documents, integrated with their claims workflow.
Technologies Used
Results Delivered
Sector Experience That Reduces Risk
We move faster when we understand your constraints, regulators, and operational realities.
Financial Services
Risk modeling, fraud detection, algorithmic trading
Healthcare & Life Sciences
Clinical NLP, diagnostics, drug discovery
Manufacturing
Predictive maintenance, quality control, supply chain
Retail & E-commerce
Personalization, demand forecasting, chatbots
Technology & SaaS
Product AI features, search, recommendations
Professional Services
Document intelligence, knowledge management
You Need More Than a Prototype. You Need Adoption.
Most GenAI projects stall between demo and deployment. We close that gap with delivery discipline, evaluation-first engineering, and practical change management.
Talk to a Solutions ArchitectSenior Builders Only
You work directly with senior AI engineers and architects. No bait-and-switch to junior delivery teams.
Outcome-Led Delivery
Each engagement is scoped around a business KPI and adoption metric, not just model quality benchmarks.
Evaluation-First Engineering
We build evals, guardrails, and monitoring into the first sprint so quality and safety are measurable.
Capability Transfer
Your team leaves with architecture docs, runbooks, and training to own the system after delivery.
Trusted by CTOs and Data Leaders
What teams say after moving from AI pilot to production delivery.
"Nebula didn't just build us a RAG system—they transformed how our entire organization accesses knowledge. The solution handles edge cases we didn't even think to test for. Their deep understanding of both the tech and our business context made all the difference."
Questions Teams Ask Before They Engage
Clear answers on delivery, security, ownership, and what to expect after you reach out.
What happens after we submit the contact form?
We reply within one business day with initial recommendations. If there is a fit, we schedule a strategy call and share a clear next-step plan.
Can you work through security, legal, and procurement?
Yes. We regularly support NDAs, vendor onboarding, security questionnaires, and procurement workflows for startup and enterprise teams.
Do you offer fixed-scope starter engagements?
Yes. Many clients start with an AI Opportunity Mapping Sprint or a focused Pilot Build with defined scope, timeline, and decision gates.
Will you work with our existing stack?
Yes. We are stack-agnostic and prefer integrating with your existing cloud, data, and product systems before introducing new tools.
Who is actually on the delivery team?
Senior AI engineers and architects. The people who scope your engagement are directly involved in implementation and handoff.
How quickly can we start?
Discovery can usually start within one to two weeks, depending on mutual availability and procurement timing.
Tell Us What You Need to Ship
Share your goals, blockers, and timeline. We will reply with a recommended engagement approach and next steps.
Tell Us About Your Project
Share your AI challenges and goals. We'll get back to you within 24 hours with insights and next steps.
Or reach out directly:
Have an AI Mandate This Quarter? Let's Execute It.
Start with a focused strategy call. We will align on your highest-leverage use case and define a realistic path to production.