AI Pods – Human-led,
AI-driven Software Delivery

An AI Pod is a small, human-led Software Mind team that delivers an outcome-based project using proprietary AI delivery tools. A typical AI Pod consists of a pod lead, a QA engineer and a developer. An AI SDLC engineer sets up the pod’s tooling and a CSA scopes the work before the pod starts.

An AI Pod is typically up and running within two to four weeks after signing a contract. Scoping happens first, then an AI SDLC engineer sets up the pod’s tooling, integrations and quality gates, typically in one to two weeks.

Every task moves through the same workflow: Ticket, Spec, Plan, Build, Harness, Approve and Deploy. An engineer directs multiple AI agents in parallel, while people approve plans and critical code. Our internal tool – Software Mind Analyst – checks progress, budget and Definition of Done against the code, so you see real delivery, not just closed tickets.

We measure each AI Pod against the agreed scope: percentage delivered, budget use, tasks finished to the Definition of Done and quality signals such as review time and test results. Software Mind Analyst reports these from your task tracker, the code and observability data.

Traditional IT outsourcing increases output by adding staff and billing per person, while relying on manual work. An AI Pod is a small, human-led team where each engineer directs several AI agents at once and delivers an agreed outcome, rather than hours. A Software Mind pod is usually made up of three to four people whereas a traditional team needs eight to ten.

Team augmentation adds individual contractors to your team to increase manual capacity, with billing based on headcount. AI Pods are human-led, AI-driven teams that join your team or own an outcome-based project. Throughput grows through AI agents working under human approval, not by adding staff.

Our AI Pods deliver faster because they use our tools, and those tools are removed when the project ends. If you need to stay on your own platforms, we can provide AI SDLC specialists who can work with your toolchain.

You keep what the pod delivered. What we build in your toolchain is yours, and Software Mind’s tools roll off when the project ends.

You can, but you would have to build the workflow around them: observability, token and cost control, governance, compliance, Jira and Confluence integration, a knowledge base and agent orchestration. We have already built and tested a system that an AI Pod brings to your project.

Software Mind Code is our AI development harness and one of the tools our AI Pods use. Our accelerators – Software Mind Blueprint, Software Mind Shift and Software Mind Lift – are configurations of it, each with its own workflow and tools. We don’t sell or license it, and it rolls off when the project ends.

Our AI Pods use the model that best fits each task’s needs for cost, quality and privacy: frontier models such as Claude, GPT and Codex, local large language models such as Llama, Mistral, Qwen and DeepSeek, and secure, fine-tuned small language models.

Every task passes automated quality and governance gates that include gates: security scanning, compliance checks, standards enforcement and a complete audit trail of all AI actions. Gates are configurable for each project, with stricter controls for sensitive areas such as authentication and payments, and are updated as regulations and models change.

AI Pods work from your ticketing system. Each request becomes a ticket, AI agents produce a specification and an implementation plan, and an engineer approves the plan before coding and again before merging, so people stay in control of key decisions.

Our AI Pods are built for domains that demand security and quality: financial services with strict data residency, healthcare, the public sector, telecom, regulated iGaming and betting, and critical legacy modernization.

No. We don’t sell our tools. We use them to deliver your outcome faster, and that is what you pay for. If you need to stay on your own platforms, we can provide AI SDLC specialists who work in your toolchain.