Knowledge Base
Frequently Asked Questions
Find answers about our engagement models, pricing, timelines, and how we work. Can't find what you're looking for? Ask us directly →
General
How fast can a team start?
Consulting engagements can start within a week. PODs and staff augmentation typically have engineers contributing within two to four weeks of signing.
What if I do not know which model I need?
Most people do not. Describe the problem and we will recommend the model. If it is not us, we will tell you.
Are these full-time dedicated engineers?
Yes. Staff augmentation and POD engineers work full time on your product. They are not shared across clients.
What if the engagement is not working?
We build in feedback checkpoints and do not lock you into long contracts. If something is not working, we address it immediately or adjust the model.
Do you work with early-stage startups?
Our typical clients are US-based companies with 50 to 2,000 employees and $10M-$100M or more in revenue. Pre-revenue startups are typically not the right fit unless they have already secured funding.
How is Sonatafy different from other nearshore firms?
Every engagement is led by a US principal engineer. Engineers are senior only (8 to 10+ years). We own delivery outcomes, not just hours.
What contract terms do you offer?
We do not require long term commitments. Engagements start with a manageable initial term and continue month to month after that. No 12 month lockups.
Who owns the intellectual property?
You do. All code, documentation and deliverables produced during an engagement belong to you. This is standard in every Sonatafy contract.
Where are your engineers located?
Our engineering organization is based across Latin America, with the largest concentration in Mexico, Colombia and Argentina. Every engagement is led by a US based principal engineer and all engineers work US business hours.
How do you handle security and compliance?
All engineers work within your environments, follow your security policies and sign NDAs. We support SOC 2, HIPAA and other compliance frameworks depending on client requirements.
How do you communicate day to day?
Our teams integrate into your existing tools including Slack, Teams, Jira, GitHub and whatever your stack is. Engineers attend your standups, sprint ceremonies and planning sessions as if they were internal.
How do you measure delivery performance?
We track cycle time, PR throughput, sprint completion rate, defect escape rate and time to first deploy. Clients receive regular delivery reports tied to business outcomes, not just activity metrics.
Can we talk to current or past clients?
Yes. We provide references from clients in SaaS, healthcare, fintech and manufacturing who can speak directly to delivery quality, team reliability and communication.
Managed Delivery PODs
How much does a Managed Delivery POD cost?
POD engagements typically range from $25K to $60K per month depending on team size and scope.
How quickly can a POD start delivering?
Most PODs complete onboarding and begin their first sprint within 2 to 3 weeks.
Can we scale the POD up or down?
Yes. PODs can scale from 2 to 6 engineers depending on backlog size and delivery velocity requirements. Scaling is flexible after an initial stabilization period.
What if a POD is not the right fit?
We will tell you in the first conversation. If your architecture is sound and you just need capacity, staff augmentation may be better. If you lack technical direction, consulting comes first.
What does the US principal engineer actually do?
The principal engineer owns delivery outcomes for the POD. They lead architecture decisions, coordinate AI tooling, run code reviews, manage sprint execution and serve as the single point of accountability between Sonatafy and your leadership team.
What tech stacks do your PODs support?
PODs support most modern stacks including React, Node, Python, .NET, Java, Go, AWS, Azure and GCP. We match engineers to your stack rather than forcing a default.
How is a POD different from a traditional outsourced team?
Traditional outsourced teams give you hours. A POD gives you end to end backlog ownership. The principal engineer owns the outcome, not just the activity. That means architectural accountability, sprint commitments tied to business results and AI embedded execution across the full lifecycle.
Do PODs integrate with our internal engineering team?
Yes. PODs are designed to operate as an extension of your team, not a separate silo. They attend your ceremonies, work in your repositories and follow your development standards.
What happens during onboarding?
The first two weeks include codebase immersion, architecture review, environment setup, backlog assessment and alignment on sprint cadence. The principal engineer leads this process to ensure the POD is delivering meaningful work by sprint one.
Can a POD own an entire product or feature area?
Yes. Many clients assign PODs full ownership of a product vertical, feature area or platform layer. The POD manages the backlog, sprint planning and delivery end to end.
Staff Augmentation
How senior are the engineers?
Every Sonatafy engineer has 8 to 10+ years of production experience. No junior rotation. No bait and switch.
How quickly can engineers start?
Engineers are typically matched within 3-5 weeks and contributing to sprint work within 2 to 3 weeks.
What happens if an engineer is not a good fit?
We replace engineers quickly at no additional cost. Our 95%+ retention rate means this rarely happens.
Do staff augmentation engineers work in our time zone?
Yes. All Sonatafy engineers work during US business hours with full overlap for standups, planning, and pairing sessions.
How much does staff augmentation cost?
Individual LATAM engineer placements typically range from $8K ($46/hr) to $12.5K ($72/hr) per month depending on seniority, specialization and engagement duration. US principal engineers are available at $150, $225/hr.
Do we manage the engineers directly?
Yes. Staff augmentation engineers report to your engineering managers and follow your sprint process. Sonatafy provides onboarding support, performance monitoring and replacement guarantees, but day to day direction comes from your team.
Can we place more than one engineer at a time?
Absolutely. Many clients place two to five engineers simultaneously across different teams or product areas. Volume placements can begin on a staggered schedule based on your onboarding capacity.
Is there a contract to hire or conversion option?
No. Sonatafy does not offer contract to hire conversion. Our engineers are full time Sonatafy team members. This is what allows us to maintain retention rates above 95 percent and guarantee consistent quality.
What if our needs change mid engagement?
You can scale up, scale down or change specialization requirements at any time after the initial stabilization period. We build flexibility into every engagement.
Consulting
How long does a typical consulting engagement last?
Most engagements run 4 to 8 weeks for diagnosis and recommendation. Fractional CTO engagements can extend for several months depending on scope.
Do we have to commit to a Managed Delivery POD afterward?
No. Consulting is a standalone engagement. If a POD is the right next step, you hear that recommendation, but there is no obligation.
What deliverables do we receive?
Every consulting engagement produces an executive summary, architecture assessment, prioritized roadmap, risk analysis, and go-forward staffing recommendation.
How much does a consulting engagement cost?
Most consulting engagements range from $5K to $25K per month depending on scope. Fractional CTO engagements are priced monthly based on time commitment.
Who from our team needs to be involved?
We typically need access to your CTO or VP of Engineering, one or two senior engineers and a product leader. Total time commitment for your team is usually five to eight hours across the engagement.
What is a fractional CTO engagement?
A fractional CTO provides senior technical leadership on a part time basis, typically two to three days per week. This includes architecture oversight, team mentoring, vendor evaluation and technology strategy, without the cost of a full time executive hire.
When should we choose consulting over a POD?
If you are unsure whether the problem is architectural, organizational or capacity related, start with consulting. A four to eight week diagnostic gives you clarity before committing to execution resources.
What happens if the assessment uncovers major issues?
We present findings with a prioritized remediation roadmap, risk ratings and recommended next steps. You decide what to act on. There is no pressure to engage Sonatafy for execution, though we can provide a scoped proposal if you want to move forward.
Platform Enablement
How long does a platform enablement engagement take?
Most engagements run 8 to 10 weeks from assessment through handoff. First improvements are typically visible within 4 to 6 weeks.
Will this disrupt our product development?
No. Sonatafy engineers work on the platform layer in parallel with your product team. Product delivery continues uninterrupted.
What happens after the engagement ends?
Every engagement includes documentation, pair programming sessions, structured handoff, and 60 days of post-handoff support.
How much does platform enablement cost?
Platform engagements typically range from $15K to $40K per month depending on scope.
What does platform enablement actually include?
It covers CI/CD pipeline optimization, testing infrastructure, deployment automation, monitoring and observability, environment management and developer experience improvements. The exact scope is defined during the initial assessment.
How do we know if we need platform enablement?
Common signals include slow deployments, unreliable test suites, frequent production incidents, long onboarding times for new engineers and teams spending more time on infrastructure than product work.
Do we need a dedicated platform team first?
No. Sonatafy provides the platform engineering expertise for the engagement and structures the handoff so your existing engineers can maintain the improvements. If you decide to build a permanent platform team later, the documentation and architecture we deliver make that transition easier.
How do you measure the impact?
We baseline deployment frequency, lead time, change failure rate and mean time to recovery at the start of every engagement. Progress is tracked against those baselines throughout, with a final report comparing before and after metrics.
Can platform enablement run alongside a POD engagement?
Yes. In fact, this is one of the most effective combinations. Platform enablement stabilizes the infrastructure layer while the POD focuses on product delivery. AI tooling delivers the most value when the underlying pipelines are reliable.
Data Transformation & AI
Do we need clean data before starting an AI project?
No. The first phase of every AI engagement is data assessment and governance. We build the foundation, then the intelligence layer.
How long does a full data transformation take?
Foundation engagements typically run 3 to 6 months. The first executive dashboards and governed data products are usually delivered within 6 to 8 weeks.
Can you work with our existing AI initiatives?
Absolutely. Many clients come to us with proof-of-concepts that stalled before reaching production. We assess what exists and build the path to production-grade deployment.
What AI models do you use?
We are model-agnostic. Depending on requirements, we deploy OpenAI, Anthropic, open-source models, or domain-specific fine-tuned models. The choice depends on cost, latency, compliance, and accuracy requirements.
How much does an AI and data engagement cost?
Data foundation and transformation engagements typically range from $20K to $50K per month depending on data complexity, source count and compliance requirements.
How do you measure ROI on AI initiatives?
Every engagement starts with defined business outcomes, whether that is reduced manual processing time, improved forecast accuracy, faster reporting cycles or operational cost reduction. We track measurable impact against those baselines, not vanity metrics.
What is agentic AI and do you build it?
Agentic AI refers to systems that take action autonomously within defined boundaries, not just analyze and recommend. Yes, we build agentic workflows including automated data pipelines, intelligent escalation systems and self optimizing processes, all under human oversight and governance frameworks.
How do you handle data security and privacy?
All data stays within your infrastructure unless explicitly agreed otherwise. We follow encryption at rest and in transit standards, role based access controls and compliance frameworks including SOC 2, HIPAA and GDPR as applicable.
Do we need a data engineering team in place?
No. Sonatafy provides the data engineering expertise as part of the engagement. If you have existing data engineers, we work alongside them and structure the handoff so they can maintain and extend what we build.
What is the difference between a proof of concept and production deployment?
A proof of concept validates that an AI approach works with your data. Production deployment means it is integrated into your systems, monitored, governed, scalable and maintained. Many clients come to us with POCs that stalled before reaching production. We specialize in closing that gap.
AI Process Automation
How long does a typical automation engagement take?
Discovery takes 2 to 3 weeks. Pilot automations are delivered within 4 to 6 weeks. Full platform integrations run 2 to 4 months depending on complexity and number of systems.
What systems can you integrate with?
We integrate with CRM (Salesforce, HubSpot), ERP (NetSuite, SAP), HRIS (BambooHR, Workday), support (Zendesk, Intercom), and custom internal platforms. If it has an API, we can connect it.
Do we need to replace our existing tools?
No. Process automation connects the systems you already use. The goal is to eliminate manual handoffs between them, not to replace them with new tools.
What ROI should we expect?
Most clients see 40 to 60% reduction in manual processing time within the first 90 days. Executive dashboards provide real-time visibility that previously required hours of manual compilation.
Can you automate processes that involve legacy systems without APIs?
Yes. We build custom middleware, screen scraping adapters, and file-based integrations for legacy platforms that lack modern API support.
Who owns the automations after the engagement ends?
You do. All automations, integrations, and dashboards are built on your infrastructure with full documentation and knowledge transfer included.
How much does a process automation engagement cost?
Discovery starts at $20K. Pilot automations start at $15K. Executive dashboards start at $30K. Full Connect phase engagements typically range from $20K to $50K per month depending on the number of systems and complexity of integrations.
Do we need to document our current processes before starting?
No. The Discovery phase includes a full process audit where we map your systems, identify bottlenecks, score automation opportunities and document everything. You provide access. We do the mapping.
Can you automate processes across multiple departments?
Yes. Most engagements span departments because that is where the manual handoffs live. Common cross-department automations include sales to finance reconciliation, HR onboarding across IT and project management systems, and support ticket routing that connects customer success with engineering.
What happens if an integration breaks after launch?
Every integration includes error handling, retry logic, monitoring and alerting. If something fails, the system notifies your team and ours. Ongoing retainer engagements include proactive monitoring and rapid response. Post-engagement support is available for clients not on retainer.
How do AI agents differ from traditional workflow automation?
Traditional automation follows fixed rules: if this, then that. AI agents evaluate context, handle exceptions, learn patterns and make decisions within defined boundaries. An automation routes a ticket to a queue. An AI agent reads the ticket, classifies urgency, assigns it to the right person, drafts a response and flags the pattern if it keeps recurring.
Do you provide ongoing support after the engagement ends?
Every engagement includes documentation, knowledge transfer and structured handoff. For clients who want continued optimization, monitoring and new automation deployment, we offer monthly retainer engagements scaled to your needs.
AI in Delivery
Does AI replace engineers on the team?
No. AI augments engineers by automating repetitive tasks like boilerplate generation, test scaffolding, and code review triage. Engineers focus on architecture, business logic, and production decisions.
What AI tools do your teams use?
Our engineers use a combination of GitHub Copilot, GPT-based tools like ChatGPT and Claude, and IDE-integrated tools such as Cursor and Codeium. We also leverage AI for test generation, code review, security scanning, and documentation, supported by custom prompt libraries tailored to each engagement. The key is that these tools are coordinated across the full delivery lifecycle to drive outcomes, not just individual productivity.
How do you measure the impact of AI in delivery?
We track cycle time reduction, PR throughput, defect escape rate, and time-to-first-deploy. Clients typically see 30 to 50% improvement in lead time within the first 60 days.
Is AI applied to every engagement?
Yes. AI is embedded across every Sonatafy engagement as a delivery standard, not an optional add-on. Every phase of the SDLC has documented AI use cases.
Do we need to provide AI tooling?
No. Sonatafy provides all AI tooling as part of the engagement. If your organization has existing tools or policies, we integrate with those instead.
What about code security and IP when using AI?
All AI-generated code goes through the same review, testing, and security scanning as human-written code. We do not use tools that train on client codebases without explicit consent.
How does AI embedded delivery differ from hiring engineers who use AI on their own?
Individual engineers choosing their own AI tools creates fragmentation. AI embedded delivery means a single delivery owner selects and coordinates AI tooling across every phase of the SDLC, from sprint planning through deployment. The difference is structural. Coordinated AI application under one accountable owner produces 30% or greater lead time reductions. Uncoordinated adoption often increases rework.
What phases of the software development lifecycle does AI cover?
AI is embedded across all seven phases: idea generation, functional definition, design, sprint planning, development, testing and QA, and deployment and optimization. That is 28 documented use cases, all coordinated by the principal engineer who owns delivery for the engagement.
Can we see which AI tools are being used in our engagement?
Yes. The principal engineer documents all AI tooling decisions and shares them with your team. There is full transparency into what tools are being used, where in the lifecycle they are applied, and how they are impacting delivery metrics.
How do you prevent AI generated code from introducing technical debt?
All AI generated code goes through the same architecture review, code review, testing and security scanning as human written code. The principal engineer enforces code quality standards and ensures AI output aligns with the engagement's architectural framework. AI accelerates delivery. It does not bypass quality gates.
What training do your engineers receive on AI tooling?
Every Sonatafy engineer is trained on AI embedded workflows before joining a client engagement. This includes code generation, refactoring, test scaffolding, documentation, security scanning and prompt engineering best practices. AI proficiency is a hiring standard, not an optional skill.
AI Solutions
Where should we start with AI?
Start with your data. If your data is fragmented, duplicated, or ungoverned, AI models will produce unreliable outputs. Our Data Transformation offering builds the foundation first.
What is the difference between AI in Delivery and AI Process Automation?
AI in Delivery embeds AI tools into how our engineering teams build software faster. AI Process Automation connects your business systems and eliminates manual handoffs between them. Different problems, complementary solutions.
How long before we see ROI from AI investments?
Process automations typically show measurable ROI within 60 to 90 days. Data transformation foundations take 3 to 6 months but unlock compounding value across every subsequent initiative.
Do you build custom AI models?
When needed, yes. But most engagements leverage existing foundation models (GPT, Claude, open-source LLMs) with custom fine-tuning, prompt engineering, and RAG pipelines tailored to your domain.
Can you work with our existing AI initiatives?
Absolutely. Many clients come to us with proof-of-concepts that stalled before reaching production. We assess what exists, identify gaps, and build the path to production-grade deployment.
What industries do you have AI experience in?
Fintech, Healthcare, SaaS, and PE-backed portfolio companies are our primary verticals. Each has specific compliance, data governance, and integration requirements that our teams know well.
How do you ensure AI outputs are accurate and trustworthy?
Every AI system we deploy includes validation layers, human oversight checkpoints and monitoring for output quality. We do not ship AI that operates without guardrails. Accuracy thresholds are defined at the start of the engagement and tracked throughout production operation.
What compliance frameworks do you support for AI deployments?
We build AI systems that operate within SOC 2, HIPAA, GDPR and industry specific regulatory frameworks as required. Data handling, model access controls and audit trails are built into the architecture from the start, not added as an afterthought.
What is the difference between a proof of concept and production AI?
A proof of concept validates that an AI approach works with your data in a controlled setting. Production AI means the system is integrated into your workflows, monitored for performance, governed for compliance, scalable under real load and maintained over time. Most AI initiatives stall between these two stages. Closing that gap is a core Sonatafy capability.
How much does an AI solutions engagement cost?
AI engagements vary widely depending on scope. Data transformation foundations typically range from $20K to $50K per month. Process automation pilots start at $15K. AI agent and copilot deployments are scoped during the Discovery phase based on complexity and integration requirements.
Do we need a dedicated AI or data team in place before starting?
No. Sonatafy provides the full engineering team for the engagement. If you have existing data or AI engineers, we work alongside them and structure the handoff so they can maintain and extend what we build. If you do not, we deliver a production system with documentation and support that does not require AI specialists to operate.
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