1–2 weeks · fixed scope
AI Strategy & Discovery Sprint
Teams validating an AI opportunity before committing a budget.
- Use-case and ROI workshop
- Data and systems audit
- Architecture blueprint
- Risk and compliance review
- Build plan with estimates
Services
AI development services, built for production.
Nine specialist capabilities delivered by one senior team. Whether you need a cited answer engine over 50,000 documents, an agent that acts safely in your systems or a full AI product, we own the outcome end to end.
All services
RAG Development
Grounded answers from your documents, with citations and access control.
- Answers in under 2 seconds across 50,000+ documents
- Every answer cites its source passage
- Access control enforced down to the document
AI Agent Development
Agents that use your tools, remember context and ask before acting.
- Hours of manual operations handled by agents
- Human approval before any sensitive action
- Persistent memory across sessions and restarts
Document AI & Anonymization
Turn scanned, messy documents into clean, compliant, searchable data.
- 98% PII detection on multi-jurisdiction legal data
- 100% data-protection and OHADA compliance
- Scanned archives converted into RAG-ready JSON
AI Workflow Automation
Connect AI to the tools your teams already use.
- Leads and tickets handled in minutes, not days
- Fewer manual hand-offs and copy-paste errors
- Workflows your team can see, edit and trust
Voice AI Agents
Natural voice conversations on phone and WhatsApp, around the clock.
- Round-the-clock coverage without adding headcount
- Instant answers to routine calls
- Clean hand-off to people with full context
AI SaaS & Product Development
From AI idea to a product customers pay for.
- An MVP in weeks, built to scale
- ~90% lower token costs with prompt caching
- Subscription billing live from day one
LLM Integration & Optimization
The right model, wired in securely, at the right cost.
- Model choices backed by evaluation, not hype
- Lower latency and token spend
- Enterprise-grade access, logging and data residency
AI Strategy & Audits
Senior guidance before you build, and proof after you ship.
- A clear, prioritized AI roadmap
- Independent evidence of quality and risk
- A team that can build and run AI with confidence
Machine Learning & Computer Vision
Predictive models and vision systems built around measurable accuracy.
- 95%+ backtested accuracy on a real-time prediction model
- Medical image classification with transfer learning
- Models deployed with monitoring, not left in notebooks
Not sure where to start?
Most projects combine two or three capabilities.
A legal platform pairs document AI with RAG. A support line pairs voice agents with automation. A SaaS feature pairs LLM integration with product engineering. We design the combination around your outcome, then deliver it as one system.
How we work
A proven path from idea to production.
Clear milestones, weekly demos and evaluation at every step. Most production builds go live in 4 to 12 weeks.
- 01Week 1
Discover
A free strategy call, then a discovery sprint: goals, users, data, systems, constraints and the metrics that define success.
You get: Discovery brief and success criteria
- 02Weeks 1–2
Architect
We design retrieval, models, tools, security and compliance boundaries, and agree an evaluation plan before writing production code.
You get: Architecture blueprint and fixed-scope proposal
- 03Weeks 2–8
Build
Milestone-based sprints with weekly demos and a shared repository from day one. You see working software every sprint.
You get: Working increments every sprint
- 04Continuous
Evaluate
Golden datasets, automated evaluations, edge-case and safety testing, plus latency and cost budgets checked on every release.
You get: Evaluation report
- 05Final sprint
Launch
Deployment to your cloud or ours, monitoring, runbooks, documentation and a hands-on handover to your team.
You get: Production system and documentation
- 06Ongoing
Scale
Optional retainer for new use cases, model upgrades, quality improvements and cost optimization as usage grows.
You get: Roadmap and continuous improvement
Engagement models
Flexible ways to work, one standard of delivery.
Start small with a discovery sprint or an audit, or go straight to a production build. Most projects start from $5,000, scoped after a free strategy call.
4–12 weeks · milestone-based
Production Build
A defined RAG platform, AI agent, automation or AI product, delivered end to end.
- Architecture and full build
- Evaluation suite and QA
- Security and compliance controls
- Deployment and monitoring
- Documentation and handover
Monthly retainer
Dedicated AI Engineering
Product and platform teams with an ongoing AI roadmap and no time to hire.
- Senior AI engineering capacity
- Weekly planning and demos
- Continuous evaluation and monitoring
- Model and cost optimization
- Scale up with vetted specialists
1–3 weeks · fixed scope
AI Audit & Evaluation
An existing LLM, RAG or agent system that underperforms or is changing hands.
- Architecture and code review
- Answer-quality evaluation
- Security, PII and compliance review
- Cost and latency analysis
- Prioritized remediation report
Not sure which model fits? A free 30-minute call is enough to decide.
Book a free strategy callFAQ
Questions buyers ask us.
Can't find your answer? Ask us on a free strategy call or send a short brief.
What does Retrieva Labs build?
We design and build production AI systems: enterprise RAG platforms and AI search, AI agents and multi-agent systems, document AI and PII anonymization, workflow automation and voice agents, AI SaaS products, LLM integrations and custom machine learning. Most of our work is for document-heavy and regulated teams in legal, government, healthcare and finance, and for SaaS companies shipping AI features.
How much does an AI development project cost?
Every engagement is scoped after a free strategy call, because cost depends on your data, integrations and compliance needs. Most projects start from $5,000. Defined builds run on fixed-price milestones, and ongoing work runs on a monthly retainer, so you always know what you're paying for.
How long does it take to build a RAG system or an AI agent?
A discovery sprint takes one to two weeks. Focused pilots usually ship in three to six weeks, and enterprise platforms with multiple data sources, access tiers and compliance requirements typically take eight to twelve weeks. You see working software at the end of every sprint.
How do you keep our data private and secure?
Privacy is designed in, not added later. We anonymize personal data before it is indexed or sent to a model, enforce role-based access at query time, encrypt data, log access, and can deploy inside your own cloud or on-premise with open-weight models when data must not leave your environment. We sign an NDA before discovery whenever you need one.
Which models and platforms do you work with?
We are model-agnostic: Claude, GPT, Gemini, Llama, Mistral and others, through direct APIs, Amazon Bedrock, Azure OpenAI or Google Vertex AI. We integrate with your existing stack on AWS, Azure or Google Cloud, and with your databases, CRMs and internal APIs.
Who owns the code and intellectual property?
You do. All source code, prompts, evaluation datasets, models and documentation we create for you are delivered to your repositories and owned by you.
Taking on new projects
Let’sbuild.
Have an AI project in mind? Let’s make it real.
Book a free 30-minute strategy call with our founder. You’ll leave with a clear view of the right architecture, timeline and next step, whether or not we work together.
- Reply within 24 hours
- NDA before you share anything confidential
- You own the code, prompts and documentation
- Hours overlap with US, UK, EU and Gulf teams