Forward-Deployed Engineering
We start with the workflow, not the technology.
We don't ask 'What AI can we build?' We ask 'Where is the workflow breaking?' Here is our complete methodology from initial friction audit to production-grade, self-sustaining software assets.
The FDE Philosophy
Why Forward-Deployed Engineering matters.
Standard software agencies stay isolated behind Jira tickets. Research labs create isolated demos. Cubic AI deploys technical engineers directly into your operational environment.
Frontline Operator Immersion
We shadow the people entering data, handling support tickets, and fulfilling orders. We uncover the unspoken workarounds that never make it into enterprise specs.
In-Situ System Integration
We build inside your existing tools—PostgreSQL databases, custom CRMs, internal APIs, and messaging channels. Your team never has to adopt another disconnected dashboard.
Production Telemetry & Asset Ownership
Every deployment includes hard operational logging: latency, error rates, staff hours reclaimed, and customer conversion. You own the code, the models, and the assets.
Core 6-Stage Loop
From operational bottleneck to production business outcome.
Inspect each stage of our forward-deployed execution framework below.
Operational Problem & Bottleneck
Work stalls between siloed software. Frontline staff waste hours on manual copying, delayed handoffs, and silent data leakage.
Deployed & Scaled Production System
Software and AI operating natively inside existing workflows. Measurable time reclaimed, 100% structured data capture, and clear ROI.
Discover — Shadow the frontline operators, not just management.
Assumptions made in conference rooms that miss informal workarounds, manual data re-entry, and staff friction.
- Observe operators navigating legacy software, spreadsheets, and messaging chats in real time
- Document unwritten procedural exceptions and edge cases that cause silent failure
- Map user permissions, security boundaries, and data governance limits upfront
Front desk spent 45 minutes manually copying WhatsApp inquiries into separate hospital EHR and billing portals.
Observed exact fields required by medical staff to design a unified ingestion schema with zero double-entry.
Engagement Methodology
How We Work With a Customer
From first conversation to hardened software in your production environment. A phased, low-risk engagement designed to prevent wasted engineering spend.
Discovery
Understand the people, workflow, systems and business objective.
1-2 short interviews with workflow operators
Day 1 – 3
Bottleneck audit & project scope
Enterprise Co-Engineering
We don't replace your IT team. We work with it.
Your company may already have developers, cloud infrastructure, cybersecurity and internal systems. We work alongside those teams to move an ambiguous AI use case from discovery to production.
Internal IT Team
- Core Infrastructure
- Security & Compliance
- Governance & Access
- Core Enterprise Systems
Cubic AI (FDE Team)
- Workflow Discovery
- Rapid Prototyping
- System Integration Plugs
- AI & Agentic Engineering
We write clean, typed, documented code that adheres to your engineering standards, passes vulnerability audits, and can be handed over completely.
“Why do we need an external AI company if we already have IT?”
1. Protects Existing Product Roadmaps
Your internal engineers are already 100% committed to core roadmap features, customer tickets, and uptime. We take the ambiguous R&D burden off their plates.
2. Specialized AI Pipeline Expertise
Building production-grade retrieval architectures, prompt evaluation loops, token budgets, and agentic error-recovery takes specialized reps.
3. Rapid Delivery Without Technical Debt
We go from workflow diagnosis to a deployed pilot in weeks rather than multi-quarter committee cycles, adhering strictly to your security guidelines.
Operating Principles
Why Work With Cubic AI?
We are built specifically for businesses that want practical, production-ready AI outcomes rather than endless slide decks or generic agency retainer models.
Problem-first
We start with the workflow, not the technology. If a problem doesn't need AI, we will recommend simpler automation.
Deployment-focused
We build for real operational environments, not just conference demos or isolated Jupyter notebooks.
Vendor-neutral
We choose the appropriate technology for the problem — evaluating open models, proprietary APIs, and standard software objectively.
Integration-first
We work with existing systems rather than forcing businesses to rip and replace what already works.
Measurable
We define concrete operational success metrics before writing code and track them after deployment.
Product-minded
Repeated customer problems become reusable, battle-tested software assets rather than one-off throwaway scripts.
Have an operational bottleneck worth fixing?
Schedule a direct 45-minute discovery consultation with our forward-deployed engineering leads. We'll map your workflow and provide a clear technical diagnosis.