Five software development outsourcing companies, how each one sells delivery, and the contract terms to settle before the first sprint
In Deloitte’s 2024 Global Outsourcing Survey, 70% of surveyed organizations had brought part of a previously outsourced scope back in-house within five years. The leading reasons were better control over service quality and growth of in-house capability.
Whether a buyer can act on either reason depends on what the original contract required, including code ownership, current documentation, and a handover plan, and those terms are set before the first sprint.
Any shortlist of software development outsourcing companies should therefore be compared on ownership, named staffing, reporting, AI pricing, and handover before reputation. This article maps five vendors to the four ways outsourcing is bought, then lists the terms to settle.
Key takeaways
- Match the buying model to how much delivery management your team wants to keep
- Require monthly reporting on metrics your team chooses, measured against a baseline set before work starts
- Test every AI claim against the invoice, since 26% of organizations using AI in outsourced services report lower vendor costs, according to the Deloitte survey
- Write ownership of code, documentation, and environments into the contract before the first sprint
4 ways to buy software development outsourcing
Software development outsourcing is bought in four models: staff augmentation, a dedicated team, a managed service measured against service-level agreements, or a subscription priced on output.
Deloitte’s 2024 survey revealed that 67% of executives report adopting managed or operate services, up from 45% two years earlier. The model decides who manages daily work, who carries delivery commitments, and what you have to untangle when the contract ends.
MODEL
Who manages daily work
Who owns delivery commitments
Best for
Exit exposure
Staff augmentation
Your team
Your team
A strong internal delivery lead and a skills gap
Context sits with individual engineers
Dedicated team
Shared between vendor lead and your product owner
Shared
A stable roadmap that needs continuity
Team continuity and documentation
Managed service
Vendor, against service levels
Vendor
Systems already in production
Runbooks and tooling the vendor operates
Subscription or output-priced
Vendor, with expert supervision
Vendor, within metered capacity
Repeatable work streams with measurable output
Agents and workflows built on the vendor’s platform
The model also shapes satisfaction. In the same survey, 88% of organizations using managed or operate services reported that their outsourced services meet or exceed expectations, against 71% of those that don’t.
5 software development outsourcing companies and how each one sells delivery
Wizeline, Globant, EPAM Systems, SoftServe, and Andela each sell a different version of outsourced delivery. The table shows what you buy and what you keep.
company
How you buy
What you keep on exit
Reporting to require
Wizeline
AI DLC program, then Builder Pods on a fixed fee per pod
Code and documentation in your own environment
Cycle time and throughput against a baseline, plus spend and usage telemetry each sprint
Globant
AI pods on a monthly subscription metered in tokens
Work product; agent portability to confirm
Token use mapped to deliverables
EPAM Systems
AI/Run engineering practice with measurement built in
Process and tooling inside your GitHub setup
Productivity baselines and adoption dashboards
SoftServe
Managed services against service-level agreements
Runbooks and monitoring configuration
Service-level compliance reports
Andela
Individual engineers or teams placed with your company
Delivery context held by named engineers
Placement and replacement records
1. Wizeline
Wizeline delivers outsourced software engineering as Builder Pods: lean teams of about five, made up of an AI solution and integrations lead, a product manager, an AI application lead, and two full stack engineers, with quality assurance, design, and DevOps work built in. The pods run inside the client’s own environment, in the development tools and terminals engineers already use, including Cursor, Codex, and Claude Code. Teams in Mexico, Colombia, Argentina, and Romania overlap US and European business hours.
The AI DLC harness is the control layer between engineers and AI agents. It routes each task to a model, caps spend, meters tokens per user and per application, and keeps an audit trail of agent output. That turns the AI pricing and reporting terms into data the client can check rather than promises it has to accept.
Buyers can enter at the stage that matches where their delivery process stands. An AI DLC Readiness Assessment of two to four weeks models the effect on cycle time and throughput, which gives the contract’s reporting term a baseline set before work starts. A proof of concept of up to four weeks and an Accelerator of eight to 12 weeks then deploy the harness in the client’s infrastructure, and Managed Practice keeps Builder Pods running production support, governance, and developer training.
Best suited to. Buyers that want an embedded engineering team building inside their own stack, with AI use governed and measured from the first sprint
Negotiate. A written handover plan covering code, documentation, and harness and agent configurations, with pod composition changes recorded in the statement of work
2. Globant
Globant offers AI Pods, a subscription service that combines AI agents with specialist expertise to deliver defined outcomes. The pods orchestrate agentic workflows end to end within a governed system, with experts supervising agent outputs to ensure they meet business and industry requirements.
Capacity is metered in tokens rather than hours. The catalog covers defined work streams such as legacy re-platforming, monolith decomposition, backlog acceleration, test automation, and code development.
A pilot follows three steps: define one use case, run a pod against your current benchmark, and decide on the evidence. Globant states that everything a pod produces belongs to the client, that AI-generated code goes through the client’s standard pull request reviews, and that pods report into monitoring tools such as Datadog, Splunk, and ELK.
Bain’s analysis of the model raised two open questions: how a token is defined, and whether dependence on Globant’s technology stack limits portability.
Best suited to. Buyers with repeatable, measurable work streams who are ready to pay for output rather than hours
Negotiate. A definition of a token in terms of delivered work, and transfer terms for agents and workflows if the subscription ends
3. EPAM Systems
Founded in 1993, EPAM’s AI/Run methodology covers governance of business value, organizational change management, adoption measurement, performance measurement, and role-based AI education.
The tooling includes a return on investment (ROI) impact analysis, value stream mapping, and an AI adoption dashboard integrated with management systems. EPAM’s platforms include DIAL, a generative AI orchestration platform for public and proprietary models, and EliteA, a collaboration platform for large language model (LLM) assets and quality assurance (QA) teams.
EPAM offers two engagement paths: delivering products and projects for the client, or enabling the client’s own workforce through strategy, measurement, and training. Its GitHub Agentic SDLC implementation sets baseline productivity metrics before scaling agentic workflows across repositories.
Best suited to. Large engineering organizations that want measured process change and can run an adoption program alongside delivery
Negotiate. The baseline each monthly metric is measured against, and who owns the dashboards after the engagement ends
4. SoftServe
Founded in 1993 and headquartered in Austin, Texas, SoftServe partners with Google Cloud, AWS, Microsoft Azure, Salesforce, and NVIDIA. Its managed services cover agentic platform operations (site reliability engineering, DevOps, infrastructure as code, and observability), cloud governance and FinOps, and managed application and data operations.
Named offerings include Agentic SRE, Agentic DataOps, Managed Cloud FinOps, and AI Solutions Support, each pairing automation with human oversight. Service levels define expected performance, while custom monitoring and escalation processes track delivery against those commitments.
Best suited to. Buyers that need systems run, monitored, and supported after launch more than they need new product engineering
Negotiate. The remedies and service credits that apply when a service level is missed, and who verifies the reported figures
5. Andela
Launched in 2014, Andela runs a global marketplace for technical talent, with technologists in more than 135 countries. The company now positions itself around AI-native engineering, including forward-deployed engineers, and runs an AI Academy for training developers.
Clients can take individual contractors for a blended team, a formed team they manage, or a fully managed team. Engineers integrate into the client’s internal team and its processes, which keeps day-to-day direction with the buyer under the first two options. Andela places technologists in remote contract roles, so confirm who carries employment, payroll, and compliance responsibilities.
Best suited to. Buyers that want to add senior capacity quickly and keep direction in-house, or want a vendor to manage a distributed team
Negotiate. Contract minimums, replacement terms, and any fee to convert placed engineers to direct hires
Contract terms to settle before the first sprint
Five contract terms determine how much control you retain over outsourced software development and how easily you can bring work in-house.
- Ownership. Code, documentation, runbooks, and environments sit in your accounts from day one
- Named staffing. The statement of work names the engineers and sets substitution terms
- Reporting. The vendor reports monthly on metrics your team selected, against a baseline set before work starts
- AI pricing. Productivity gains from AI reach the invoice on a schedule written into the agreement
- Handover. The exit plan covers documentation, knowledge transfer, and a transition period
Reporting deserves particular attention, as 55% of organizations cited lack of benefit realization tracking as an outsourcing challenge in Deloitte’s 2024 report. For AI, Deloitte recommends contract provisions that report AI-driven productivity gains and commit to fee reductions over time.
Named staffing protects continuity. Without it, the engineers who impressed you in interviews can be replaced after kickoff. Write substitution terms into the statement of work: notice periods, overlap between outgoing and incoming engineers, and your right to approve replacements.
AI pricing needs a schedule. Fewer than half of the executives in Deloitte’s 2024 survey are seeking price reductions from vendor AI productivity gains, which leaves most buyers without a mechanism. A schedule that states when and how gains reach the invoice turns an assumption into a term.
Handover deserves the longest clause. Among organizations exploring more insourcing, 68% cite better control over service quality and performance. A contract that documents the work as it happens keeps that option open at a lower cost.
The bottom line
Deloitte’s data shows buyers rebalancing outsourced and in-house work. The contract determines how cleanly that rebalancing can happen. Compare software development outsourcing companies on ownership, named staffing, reporting, AI pricing, and handover before comparing rates.
Wizeline’s Builder Pods run inside the client’s own tools, so ownership and handover terms start with the code already in the client’s accounts. AI DLC adds a baseline before work starts and spend and usage telemetry through delivery, which gives the reporting and AI pricing terms something to check.
If your shortlist looks strong on paper but leaves handover and ownership unanswered, the contract is where the risk sits, and it’s worth a conversation.
Frequently asked questions
How do I choose a software development outsourcing company?
Choose the buying model first, then compare vendors on five contract terms: ownership, named staffing, reporting, AI pricing, and handover. Staff augmentation leaves delivery management with your team, while managed services shift it to the vendor. A vendor that answers all five terms in writing before the first sprint has already removed most of the governance risk.
What is the difference between staff augmentation and managed services?
Staff augmentation adds engineers who work under your direction, and the relationship is transactional. Managed services hand a defined scope to the vendor, with performance tied to service-level agreements and pricing based on outcomes and volume.
Should I hire an IT consulting company or an outsourcing software development company?
An IT consulting company typically produces assessments and recommendations, and an outsourcing software development company builds and operates the software. For a modernization program, choose based on who will own the running system once the strategy phase ends.
What are the biggest risks of outsourcing software development?
The biggest risks sit in governance and transitions. In Deloitte’s 2024 survey, 46% of organizations cited poor vendor performance during transitions of services. Contracting for documented handover, named team members, and outcome metrics before work begins makes most of these risks manageable.
How do I bring outsourced software work back in-house?
Plan the return in the original contract: repositories in your accounts, documentation kept current, knowledge transfer, and a transition period. Deloitte recommends revisiting outsourcing deals that are more than three years old to reevaluate which scope is core to the business.
