01ASSESS
AI readiness and opportunity map.
2-3 weeks, fixed fee. Technology, data, and team review.
- AI opportunity map aligned to business goals
- Risk & remediation register
- Clear roadmap for what to build first
Production AI. Shipped in weeks.
MavenCode delivers production AI in 6-12 week fixed-scope sprints. From agentic automation to bespoke LLMs, we ship measurable results, not strategy decks.
Technology partners
How we workForward-deployed.
Forward-deployed.
Fixed scope.
Our engineers embed in your environment and stay accountable from the first commit to production. No open-ended consulting: every engagement is scoped and structured before work begins, and you own everything we deliver.
02SPRINT
First production result inside a quarter.
6-12 week sprints, fixed-scope, milestone-driven.
- Agentic automation for operational efficiency
- Data foundations for velocity
- LLM-powered product features
03HARDEN
MLOps that runs in production.
Monitoring, automation, reliability, and governance.
- Model monitoring & drift detection
- Security posture & compliance
- Production-ready documentation
04TRANSFER
Your team owns it. No lock-in.
Progressive enablement: the team levels up while the system gets built.
- Capability transfer by design
- Month-to-month optional support
- No vendor dependency
EMBEDDED PODS · 3-4 SENIOR ENGINEERS · FIXED-SCOPE SPRINTSBrowse all ten capabilities →
What we deliver
Ten capabilities that turn AI from concept to business value.
Every engagement ships a working system into your environment, with the monitoring and quality checks already wired up.
01 / AI Solutions
Bespoke AI, built for your use case.
Custom AI solutions including fine-tuned LLMs for specialized use cases where general-purpose models fall short.
Read more02 / AI Platform
Production infrastructure for AI at scale.
End-to-end AI platform development, from model serving to inference APIs, engineered for reliability.
Read more03 / Data Engineering
The data foundations every later sprint builds on.
Lakes, warehouses, feature stores, and streaming pipelines with governance and compliance built in.
Read more04 / Cloud Architecture
From legacy to cloud-native AI.
Migration, automation, and modern architectures that prepare your infrastructure for production AI.
Read more05 / Language & Vision
Fine-tuned LLMs and vision models.
Custom and fine-tuned models trained on your domain data. Semantic search, summarization, and document understanding.
Read more06 / MLOps
Models that run reliably in production.
Automated training, testing, release pipelines. Monitoring, drift detection, versioning, and reproducibility.
Read more07 / Agents & Workflows
Agentic automation for operational efficiency.
Intelligent agents that automate complex decision-making across intake, processing, reconciliation, and reporting.
Read more08 / Software Development
Full-stack product engineering.
Application development that turns AI capabilities into usable products your teams and customers will adopt.
Read more09 / Physical AI
AI that acts in the physical world.
Perception, control, and decision-making on robots, vehicles, and industrial equipment, with models deployed at the edge.
Read more10 / Training & Strategy
Enable your team to own what comes next.
Hands-on training, strategy workshops, and progressive enablement so AI capability stays after we leave.
Read moreUnder the hood
What production-grade actually means.
Every engagement ships against the same engineering baseline. Nothing is handed over as a prototype and called a product.
- TestedUnit, integration, and model evaluation suites that run on every change.
- MonitoredDrift detection, quality checks, and alerting wired up before launch day.
- AutomatedReproducible builds, staged rollout, and a rollback path that has been exercised.
- DocumentedArchitecture notes and operational runbooks written for your team, not for us.
- SecuredLeast-privilege access, managed secrets, and an audit trail on every decision.
- VersionedModels, datasets, and prompts tracked so any result can be reproduced later.
How it works
Four layers. One system. Built for your team.
Every engagement delivers a clear, layered architecture your team can understand, extend, and own.
L 01
Interface
How your people and systems interact with the AI.
Web appAPI gatewayNotificationsDashboard
input
L 02
Intelligence
Where the AI plans, decides, and validates results.
PlanningRoutingValidationLearningReview
AI core
L 03
Integration
The integration layer. Secure connections to all your systems.
System connectorsData standardsSecurityAudit trail
connect
L 04
Execution
Where work actually happens. AI models process your data.
AI modelsBusiness toolsData warehouseReal-time feedsCloud storage
output
Selected work
Real results, real clients.
AI systems we've built and deployed, with the numbers our clients measure in production.
+11ptsACCURACY
Automated risk assessment across 1.4M patients.
Risk prediction accuracy improved by 11 points over the previous system, with every alert linked to the evidence behind it.
Read case →
−62%FALSE ALERTS
Analytics engineering embedded with product teams.
Automated validation cut false alerts by 62%, saving thousands of review hours across the platform.
Read case →
×4.2DEPLOYMENT SPEED
Ninety-two manual processes, automated in eleven weeks.
Modern streaming pipelines replaced outdated batch jobs, and automated quality checks replaced manual review.
Read case →From the field
Insights from the field.
Lessons we've learned building AI systems, written so you don't have to learn them the hard way.
Next steps
Four ways to keep the conversation going.
01
FIXED FEE
AI Readiness Assessment
2-3 week review of your data, models, and infrastructure.
Start assessment →02
6-12 WEEKS
Production sprint
First production result inside a quarter, milestone-driven.
Scope a sprint →03
ENTERPRISE
Multi-team agreement
One contract covering several teams, with rates and terms set once.
Discuss terms →04
NO COST
Read our insights
Field notes on small models, fine-tuning, and multimodal systems.
Browse insights →Start here
Let's put AI to work for your business.
Start with a fixed-fee readiness assessment on one team or product.