AI Managed Pod
A dedicated AI engineering team. Sprint-based delivery, direct communication, full accountability. Starting at $12,000/month.
14+
Years of Experience
800+
Projects Delivered
100+
Engineers
4.9★
Clutch Rating
One-off AI projects are a start. Sustained AI development is how you build competitive advantage. The AI Managed Pod gives you a dedicated, cross-functional AI engineering team that works exclusively on your product, sprint after sprint, without the overhead of hiring, onboarding, and managing a full-time team. Your Pod learns your domain, understands your codebase, and ships AI features continuously.
The Hidden Cost of Building an In-House AI Team
Hiring AI engineers sounds straightforward. In practice, it is one of the most expensive and time-consuming decisions a growing company can make.
AI engineers cost $180K-$350K per year in the US
A senior AI/ML engineer commands $180,000-$250,000 in salary alone. Add benefits, equity, recruiting fees (20-25% of salary), and management overhead, and you are looking at $250,000-$350,000 per head, per year. For a team of three, that is $750K-$1M annually before they ship a single feature.
It takes 3-6 months to hire a single AI engineer
The AI talent market is the most competitive in tech. Posting a job, screening candidates, running technical interviews, negotiating offers, and onboarding takes 3-6 months per hire. Meanwhile, your competitors are shipping AI features every sprint.
Individual hires create single points of failure
One AI engineer cannot cover every specialization: NLP, computer vision, RAG pipelines, agent systems, MLOps, and data engineering. When they leave (and AI engineers have the highest turnover in tech), their domain knowledge walks out the door with them.
Freelancers and contractors disappear mid-project
Freelance AI developers work on multiple clients simultaneously. They have no accountability for long-term outcomes, no QA process, and no continuity between projects. When the engagement ends, so does their institutional knowledge.
The cost of waiting: Every month you spend hiring is a month your competitors are shipping AI features. At current market rates, a 4-month hiring delay for a 3-person team costs $300K+ in lost productivity, not counting the opportunity cost of features that never shipped.
The alternative: An AI Managed Pod gives you a complete, cross-functional AI engineering team in 1-2 weeks, at 40-60% less than equivalent US hires. Your Pod includes AI engineers, QA, and a Tech Lead who take ownership of delivery. Sprint-based cadence ensures you see working software every two weeks.
What Is an AI Managed Pod?
An AI Managed Pod is a dedicated, cross-functional AI engineering team that works exclusively on your product. Unlike staff augmentation (where you manage individual contractors) or freelancers (who juggle multiple clients), a Managed Pod is a self-organizing team with shared accountability for outcomes. You set the priorities; the Pod handles execution, code reviews, QA, sprint planning, and delivery.
At Salt Technologies AI, each Pod is assembled based on your specific technical requirements and AI objectives. A typical Pod includes one or more AI/ML engineers with production experience in LLMs, RAG pipelines, agent frameworks, and data engineering, plus a dedicated QA specialist and a Tech Lead who provides architecture guidance and coordinates delivery. The Pod integrates with your existing project management tools (Jira, Linear, GitHub), joins your communication channels (Slack, Teams), and operates on 2-week sprint cycles with demos and retrospectives.
Pod compositions range from Starter ($12,000/month) to Scale ($30,000/month) depending on team size and seniority mix. After a 3-month initial engagement, you can scale up, scale down, or transition development in-house with full knowledge transfer. You own all code, documentation, and intellectual property from day one.
1-2 Weeks
From Contract to First Sprint
40-60%
Cost Savings vs. US Hires
4-6 Hours
Daily US Timezone Overlap
8-14 Months
Average Client Retention
The ROI of an AI Managed Pod
A Growth Pod at $20,000/month delivers the output of a US-based team that would cost $60,000-$80,000/month in salary and overhead. Here is the math.
Scenario: Building an equivalent 4-person AI team (2 AI Engineers + QA + Tech Lead)
Option A: Hire In-House (US)
Option B: AI Managed Pod
$52,000
Saved per month
$624,000
Saved per year
72% Less
Than equivalent US team
Based on 2025-2026 US salary data for senior AI/ML engineers ($180K-$250K base) plus benefits, equity, and overhead. India-based team costs reflect fully-loaded rates including infrastructure, tools, and management. Actual savings depend on Pod size, seniority mix, and specific role requirements.
We will calculate your specific cost savings on the discovery call. Free, 30 minutes, no obligation.
Is an AI Managed Pod Right for You?
A Managed Pod is the right choice for companies that need sustained AI development capacity, not a one-time project.
- You have ongoing AI development needs, not just a one-off project
- You want a dedicated team, not rotating freelancers who disappear mid-sprint
- You need AI engineers who understand your codebase, domain, and business logic
- You want to scale AI development without the 3-6 month hiring cycle
- You have tried staff augmentation or freelancers and been burned by inconsistency
- You need AI expertise across multiple domains: NLP, computer vision, data pipelines, or MLOps
If two or more sound like you, a Managed Pod will accelerate your AI roadmap.
Most clients see their Pod outperforming expectations within the first 90 days.
Tell Us About Your AI GoalsAI Managed Pod Use Cases
See how companies use dedicated AI engineering teams to ship faster, reduce costs, and build competitive advantage.
Continuous AI Product Development
Ship new AI features, improve existing models, and iterate on user feedback every sprint. Your Pod becomes an extension of your product team with deep domain expertise in LLMs, RAG, and agent systems.
AI Center of Excellence
A dedicated team that becomes your company AI expertise hub, building chatbots, RAG systems, AI agents, and workflow automations across departments as business needs arise.
Scale After Successful PoC or Project
Transition from a one-time AI project to continuous development without the 3-6 month hiring cycle. Keep momentum after a successful proof of concept or initial build ships.
Augment Your Internal AI Team
Add specialized AI engineers to your existing team for specific capabilities (NLP, computer vision, MLOps) or bandwidth during high-priority sprints without permanent headcount.
AI-First Startup Engineering
Get a full AI engineering team from day one without the overhead of recruiting, vetting, and managing individual hires. Ship your AI-powered product faster with a team that has built production AI systems before.
Enterprise AI Modernization
Systematically add AI capabilities across your organization: internal copilots, document intelligence, process automation, and predictive analytics. Your Pod handles the technical execution while you set strategic priorities.
14+
Years of Engineering
800+
Projects Delivered
100+
Engineers on Staff
4.9
Clutch Rating
AI Managed Pod Compositions
Three Pod sizes to match your AI development velocity. Start small, scale as your roadmap grows.
Starter Pod
Ideal for focused, single-workstream AI development
$12,000/mo
Best for: Companies starting their AI journey or adding AI to an existing product with a focused scope.
Growth Pod
For teams shipping multiple AI features per sprint
$20,000/mo
Best for: Companies with an active AI roadmap and multiple features to ship per quarter.
Scale Pod
Full AI engineering team with DevOps and infra
$30,000/mo
Best for: Companies with AI as a core product differentiator and multiple concurrent projects.
Not sure which Pod size? Tell us your objectives and we will recommend the right composition in a free 30-minute call.
Which Pod Is Right for Me?What Every AI Managed Pod Includes
Six pillars of managed delivery. Every Pod, every tier. This is how we ensure consistent output and accountability.
Dedicated Cross-Functional Team
Your Pod is not a pool of rotating contractors. It is a fixed team of AI engineers, QA, and a Tech Lead who work exclusively on your product. They learn your codebase, understand your domain, and build institutional knowledge that compounds over time.
Sprint-Based Delivery With Demos
Every 2-week sprint ends with a demo of working software and a retrospective. You see progress biweekly, provide feedback, and steer priorities. No black boxes, no surprises, no waiting months for a big reveal.
Architecture Reviews and Technical Guidance
Your Tech Lead does not just manage tasks. They provide AI architecture guidance, technology recommendations, build-vs-buy analysis, and help you make informed decisions about model selection, system design, and technical trade-offs.
Your Project Management Tools, Not Ours
The Pod integrates with your existing tools: Jira, Linear, GitHub Projects, or Asana. Sprint boards, burndown charts, and progress tracking happen in whatever system your team already uses. No new tools to adopt or learn.
Direct Communication Access
Your Pod joins your Slack or Teams channels. No ticketing systems for day-to-day communication. Talk to your engineers directly, ask questions in real time, and get updates without scheduling meetings.
Monthly Progress Reports and Roadmap Updates
Beyond sprint demos, you receive monthly progress reports covering velocity trends, completed features, upcoming priorities, and Pod performance metrics. We recommend team adjustments proactively based on your evolving needs.
How the AI Managed Pod Works
Discovery and Pod Assembly
Week 1We assess your codebase, tech stack, and AI objectives. We assemble a Pod with the right skill mix for your project and define sprint priorities.
Onboarding and First Sprint
Weeks 2-3Your Pod reviews documentation, sets up development environments, integrates with your project management tools, and delivers working features in the first sprint.
Sprint Cadence
Ongoing2-week sprints with planning, demos, and retrospectives. Your Pod delivers working AI features every two weeks. You review, provide feedback, and steer priorities.
Monthly Reviews and Optimization
MonthlyMonthly progress reports, roadmap adjustments, team performance reviews, and Pod size recommendations based on your evolving needs and velocity targets.
Stop hiring. Start shipping. Get a Pod recommendation in a free 30-minute call.
Talk to Us TodayAI Managed Pod vs. Staff Augmentation vs. Freelancers
Companies hiring AI talent face three options. Here is why a Managed Pod delivers better outcomes at lower cost.
AI Managed Pod
Salt Technologies AI
Complete team with shared accountability
We manage delivery, QA, and sprints
Domain knowledge compounds over time
Built-in Tech Lead and architecture
Fixed monthly cost, no surprises
Ready in 1-2 weeks
Staff Augmentation
Individual contractors
Individual hires, you manage them
You own delivery, QA, and reviews
High turnover, knowledge walks out
No architecture guidance included
Hourly billing, costs escalate
Ready in 2-4 weeks
Freelancers
Upwork, Toptal, direct hire
Solo operators juggling clients
You manage everything end-to-end
No continuity between engagements
No QA process or code reviews
Variable quality and availability
Ready in 1-2 weeks
Results Our Pods Deliver
Across Salt Technologies' 800+ projects and 14+ years, these are the outcomes our dedicated teams consistently produce.
2-3x
Faster Feature Velocity vs. Hiring
40-60%
Cost Savings vs. US Team
8-14mo
Average Client Retention
95%+
Sprint Commitment Hit Rate
"We spent four months trying to hire two AI engineers. With Salt Technologies AI, we had a full Pod shipping features in week two. After six months, they knew our product better than most internal hires would."
VP of Engineering
Series B SaaS Company, 150 employees
AI Managed Pod: Pricing and Timeline
Starter Pod
$12,000/mo
Growth Pod
$20,000/mo
Scale Pod
$30,000/mo
Minimum Commitment
3 Months
Month-to-month after initial period
Time to First Sprint
1-2 Weeks
From contract signing to working features
What Affects AI Managed Pod Pricing
- Pod size: number of engineers
- Seniority mix: mid-level vs. senior engineers
- Hours of timezone overlap required
- Compliance requirements (HIPAA, SOC2)
Get a custom Pod recommendation and quote
Tell us about your AI objectives, current team, and timeline. We will recommend the right Pod composition, give you an exact monthly cost, and outline expected deliverables for the first 3 months.
Get Your Pod ProposalNot happy with your Pod's performance? We replace team members within 2 weeks, no questions asked.
Not ready for a call? Email your requirements to [email protected] and we will respond with a Pod recommendation within 24 hours.
AI Managed Pod Technology Stack
Our AI engineers work across the full modern AI stack. We match team skills to your technology requirements, whether you are building LLM-powered products, RAG systems, AI agents, or ML pipelines.
Why Choose Salt Technologies AI for Your Dedicated AI Team
We have been building software teams for 14+ years. Here is what makes our Managed Pods different from every other outsourcing option.
A Complete Team, Not Individual Contractors
Each Pod is a cross-functional team with shared accountability for delivery. You get an AI engineer, QA specialist, and tech lead who coordinate as a unit, not isolated contractors.
Sprint-Based Delivery With Demos
Every 2-week sprint ends with a demo and retrospective. You see working software every 2 weeks, provide feedback, and steer priorities. No black boxes or surprise deliverables.
Domain Knowledge That Compounds
Your Pod learns your codebase, business logic, and domain over time. After 2-3 months, they operate as effectively as an internal team but without the hiring and onboarding overhead.
Scale Up or Down Flexibly
After the initial 3-month commitment, you can add or remove team members with 30 days notice. Match Pod size to your current development velocity and budget.
14+
Years of Experience
800+
Projects Delivered
100+
Engineers
4.9★
Clutch Rating
AI Managed Pod: Frequently Asked Questions
How much does an AI Managed Pod cost?
What is the minimum commitment for an AI Managed Pod?
How is an AI Managed Pod different from staff augmentation?
Can I scale the AI Managed Pod up or down?
What timezone does the AI development team work in?
What project management tools does the Pod use?
Can the Pod work on multiple AI projects simultaneously?
How do you handle knowledge transfer if we bring AI development in-house?
What AI technologies does the Managed Pod work with?
How quickly can an AI Managed Pod start working on my project?
Does the Pod help with AI strategy, or only execution?
What happens if the Pod is not meeting expectations?
Choose Your Starting Point
Most clients go straight to a Managed Pod. But if you want to validate first or need a one-time project before committing to ongoing development, we have options.
AI Readiness Audit
Get a prioritized AI roadmap for your business. We identify which AI projects will deliver the highest ROI and recommend the right Pod composition to execute them.
AI Managed Pod
A dedicated AI engineering team on your product from week one. Sprint-based delivery, direct communication, full accountability. Most clients start here.
AI Chatbot or Agent Build
Start with a fixed-scope AI project. After delivery, you can transition to a Managed Pod for continuous development, new features, and ongoing optimization.
Already have an AI project in mind? Many clients start with a Proof of Concept Sprint ($8,000) to validate feasibility, then transition to a Managed Pod for production development and ongoing iteration.
No obligation to continue after any step. You own every deliverable.
View All AI ServicesWhat to Expect on the Discovery Call
30 minutes. No sales pitch. No pressure. Here is exactly what happens.
You Talk, We Listen
Tell us your AI objectives, current team setup, and biggest bottlenecks. We ask questions to understand your specific needs. This is a conversation, not a pitch.
We Recommend a Pod
Based on your goals, we recommend a Pod size, skill mix, and engagement structure. You get a ballpark cost on the call and a detailed proposal within 48 hours.
You Decide, No Rush
Review the proposal on your own time. No follow-up pressure. If it is a fit, we can have your Pod assembled and shipping within 1-2 weeks of signing.
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Ship a custom AI chatbot that actually understands your business in weeks.
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Build an AI agent that actually does the work, not just answers questions.
AI Workflow Automation
Automate the repetitive work your team hates with AI that actually gets it right.
"Our Pod shipped more AI features in their first quarter than our in-house team had delivered in the previous year. The sprint cadence and direct Slack access made it feel like they were sitting in the next room."
CTO
Healthcare SaaS Startup, 40 employees
Your Competitors Are Already Shipping AI Features Every Sprint
Get a dedicated AI engineering team in 1-2 weeks, at 40-60% the cost of US hires. We are currently assembling Pods for Q1 2026 engagements. Book a free 30-minute call before capacity fills.
AI Managed Pod
From $12,000/mo