AI services company
Turn your AI investment into measurable outcomes
Enterprise AI consulting, custom development, and managed services. From strategy to production, your team gets outcomes they can point to, not just a roadmap.
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AI projects
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brands served
98%
on-time delivery
What we build
Every AI capability your enterprise needs
From a first strategy call to production AI systems running in your stack. Pick the entry point that fits where you are today.
AI consulting services
Strategy, roadmap, and vendor selection. Get to a decision-ready AI plan in weeks, not quarters.
AI consulting services →AI development services
Custom models, agents, and integrations built to your architecture, not a template.
AI development services →Agentic AI development
AI agents that plan, act, and loop back on results. Multi-agent orchestration with governance built in.
Agentic AI development →AI solutions
Chatbots, copilots, document intelligence, retrieval-augmented generation pipelines, and predictive analytics shipped as working products.
Explore AI solutions →AI managed services
Ongoing model monitoring, retraining, and operations so your AI keeps improving after launch day.
AI managed services →Hire AI developers
Dedicated AI engineers, augmentation teams, and outsourced delivery units. Onboarded in days, not months.
Hire AI developers →The problem
Most AI initiatives stall before they reach production
You've seen the demos. You've approved the budget. But three months in, the proof of concept is still in a spreadsheet and your team is doing the same manual work they were doing before.
With Redefine
- Scoped proposal in 3 days. Sprint 1 starts within a week of sign-off
- Prioritized use case roadmap tied to your highest-cost operational pain
- Production-ready AI deployed in your stack with observable, auditable outputs
- Board-ready return on investment metrics from week 4 onward, not hypothetical projections
Without AI services
- Proof of concept sits in a Jupyter notebook. It never reaches production
- Your team can't agree on which AI use case to prioritize first
- Vendor demos look impressive but no one can scope the actual build
- Six months of budget spent, zero measurable return on investment to show leadership
Delivery process
From signed brief to live AI system in 6 weeks
Every engagement follows the same four-phase delivery framework. You always know what is happening, what your team needs to do, and what comes next.
1
Discovery and scopingDays 1 to 5: AI readiness assessment, use case prioritization, and scoped proposal
2
Architecture and designWeek 2: Data architecture, model selection, integration map, and sprint plan
3
Build and iterateWeeks 3 to 5: Sprint-based development with weekly demos and async feedback loops
4
Deploy and measureWeek 6 onward: Production deployment, observability setup, and return on investment baseline report
Readiness Assessment: Delivered Day 5
7/10
Data readiness
3
Priority use cases
$2.1M
Annual savings est.
Document classification agentHigh return on investment
Customer support automationMedium return on investment
Sales forecasting modelQuick win
Data and Model Architecture
Vector store: Pinecone: 1.2M document embeddingsReady
Large language model: Claude claude-sonnet-4-6 via BedrockApproved
Integration: Salesforce and Dynamics 365In scope
Sprint plan: 3 two-week sprints. Demo on day 14, 28, and 42
Active sprint: Day 28
Done
Retrieval-augmented generation pipeline
Guardrails layer
Auth integration
In progress
Agent routing
User interface wrapper
To do
Load testing
Quality assurance sign-off
System live: 100% uptime
94.7%
Classification accuracy
1,847
Documents processed today
$48k
Cost avoided this month
2.1s
Average response time
What you get
Built for the enterprise buyer who has been burned before
Every service we offer was designed around the same principle: AI that your team can actually rely on.
Outcome-first scoping, every time
We measure success by the business metric it changes, not the number of models deployed. Every brief starts with the key performance indicator your executive team will report.
See the AI discovery workshop →Governance and guardrails built in
Human-in-the-loop controls, audit trails, and compliance-ready outputs from day one. Not bolted on afterward.
Integrates with your existing stack
Salesforce, Dynamics 365, ServiceNow, Snowflake, and 14 more enterprise platforms.
Observability from day one
Every production deployment ships with a live metrics dashboard. You see what the model is doing, when it is wrong, and why.
From brief sign-off to live system in six weeks
One delivery rhythm on every engagement: fixed phases, weekly demos, and a board-ready return on investment baseline before handoff.
- Week 1Discovery, readiness report, and scoped proposal
- Week 2Architecture blueprint and sprint plan locked
- Weeks 3 to 5Build sprints with demos on day 14, 28, and 42
- Week 6+Production deploy, observability, and return on investment report
Senior delivery team, not a junior outsource bench
Your lead engineer has shipped production AI before. Your project manager has managed a live deployment, not just a prototype. Seniority mix is locked before you sign. See dedicated AI development teams →
Client proof
What a full digital transformation looks like
Corporate Gear
Enterprise ecommerceBusiness-to-business branded merchandise platform serving large enterprise and government accounts across North America.
The problem
Fragmented platform, poor conversion performance, and legacy infrastructure that could not support modern business-to-business workflows or scale. Manual processes across every fulfillment step.
Solution delivered
Headless ecommerce architecture with enterprise resource planning integration, full user experience redesign, A/B testing infrastructure, and data-driven personalization across the purchase journey.
- Headless replatform with Node.js and Next.js
- Enterprise resource planning and Google Analytics integration
- Klaviyo lifecycle automation and segmentation
- ADA accessibility compliance remediation
Result
$0
Annual revenue achieved through data-driven optimization, improved conversion infrastructure, and integrated marketing systems.
Platform and architecture
Production-grade AI needs infrastructure to match
Every AI system we ship is built on observable, auditable, enterprise-grade architecture. No black boxes.
Data layer
Ingestion pipelines
Vector embeddings
Feature stores
Model layer
Foundation model selection
Fine-tuning and retrieval-augmented generation
Guardrails and evaluation
Operations layer
Observability and logging
Drift detection
Retraining pipelines
Works with your stack
SalesforceAzure OpenAIDynamics 365SnowflakeDatabricksServiceNowAWS Bedrock
Why Redefine
Different things matter to different buyers
Pick the role that matches yours. The concerns that come with that seat shape how we work.
You need production AI, not another proof of concept
Your board approved the budget. Your team is capable. What you need is a delivery partner who can take a model from design to a scalable production system without creating a new legacy problem.
- Architecture review on week 1 so you see the technical decisions before code is written
- Machine learning operations and large language model operations infrastructure included, not an optional add-on
- Your team owns all intellectual property, all weights, all pipelines from day one
Other implementation partners compared to Redefine
Architecture review before Sprint 1
AlwaysRarely
Machine learning operations in base scope
IncludedAdd-on
Production observability
AutomatedManual
Intellectual property and code ownership
100% yoursLicense-based
Security, compliance, and governance: not an afterthought
You need AI that passes your security review, fits inside your existing governance framework, and does not create a new shadow information technology problem for your team to manage.
- Security operations center 2-compatible architecture options and audit-ready logging by default
- Private deployment on your cloud. No third-party data exposure.
- AI governance consulting to establish policies before models go live
Enterprise compliance stack
Data encryption at rest and in transit
Role-based access and single sign-on / multi-factor authentication integration
Human-in-the-loop override controls
Full audit trail of every model decision
Reduce the manual work your team does every day
You know which processes are slow, error-prone, and costing hours per week. You need AI that targets those exact workflows, integrates with the tools your team already uses, and is measurable by the metric you report.
- Process audit identifies the highest-cost manual workflows before you commit to anything
- AI built to connect with Salesforce, ServiceNow, and your enterprise resource planning directly
- Time-saved and cost-avoided dashboards from week one in production
Common use case return on investment benchmarks
Document processing70% faster
Customer support resolution45% faster
Invoice processing85% automated
Frequently asked questions
Honest answers to real buying questions
We scope and propose within 3 business days of receiving your brief. Sprint 1 begins within 1 week of contract sign-off. You do not wait for a long discovery phase before any work starts. Discovery is Sprint 1.
Engagements range from a focused AI discovery workshop starting at $8,500, to full enterprise AI development programs starting at $75,000. All pricing is line-item scoped before you commit. No surprises, no change-order culture. See detailed AI consulting pricing →
Yes. We have built production integrations for Salesforce, Dynamics 365, ServiceNow, Snowflake, Databricks, Azure OpenAI, and AWS Bedrock, among others. If your platform is not on that list, we scope the integration before any work begins so you know exactly what is involved.
Approximately 3 to 4 hours per week: one sprint review, async feedback on deliverables via Loom or Slack, and a final quality assurance sign-off. You do not manage developers day to day, write specs, coordinate quality assurance, or produce handoff documentation. We own all of that.
You can choose a managed services retainer covering monitoring, drift detection, retraining, and incident response. Or you can take the handoff fully: all code, all pipelines, and full documentation, and run it internally. Either path is fully supported. See AI managed services →
Start here
Tell us what your team is doing manually
Submit your brief below. We'll review your situation, identify the highest-value AI opportunity, and send you a scoped proposal within 3 business days. No commitment required to receive it.
1
Submit your brief
Tell us your team's biggest manual bottleneck
2
Call within 48 hours
A senior AI consultant reviews your situation first
3
Scoped proposal in 3 days
Line-item budget, delivery timeline, and team spec
4
Sprint 1 within 1 week of sign-off
Work starts fast, no long procurement runway
Brief received.
We'll review your situation and send a scoped proposal within 3 business days. Expect a call from our team within 48 hours.
Form
Call within 48 hours · Proposal in 3 days · Sprint 1 within 1 week of sign-off
Response in 48 hours
Proposal in 3 days
120 AI projects delivered
You own all code
Next step
Book an AI strategy call
30 minutes. A senior consultant reviews your current stack and biggest operational challenge, then tells you exactly what kind of AI investment makes sense for your situation and what it would return. No commitment. No pitch.