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Custom AI-first projects that end in production .
For companies that need custom technology for specific use cases, with diagnosis, build, and production combined from the contract. From the simple to the advanced.
Technology that turns into return on investment.
“We have 5 PoCs. None in production.”
A variation of this sentence is what we hear most. The company tested AI with a vendor, with an intern, with the innovation team, with an HR chatbot. Each PoC showed that the technology works, but none ever ran with a real client, at real volume, with SLA, integrated into the right system. The board still asks for AI strategy, the CFO still hasn’t seen a line of return, and the internal team is tired of slides.
Levver enters exactly at this point. Not to deliver another isolated PoC. To map what exists, choose a concrete bet, and cross over to production.
Six fronts. One promise.
Engagements can combine any of these fronts. Everything ends with code running in the client’s environment, with measured metrics.
AI Product Strategy
AI maturity diagnosis, mapping of opportunities by workflow, prioritization by ROI, and implementation roadmap. Typical delivery in 4 to 6 weeks.
Custom AI Build
Construction of agents, systems, and AI workflows custom-built for the client’s stack and data. Frontier or open-source models, as appropriate.
Conversational & Agentic AI
Conversational assistants and autonomous agents integrated into CRM, ERP, helpdesk, intranet, or own app.
AI Automation
Orchestration of workflows with AI applied to repetitive operational processes. Document ingestion, classification, routing, automated action.
AI-Powered Web & App
Development of Web, mobile, and backend applications with AI embedded from the design. Not traditional dev with optional AI. It’s software engineering that understands AI as a product layer. Modern stack, delivery in production.
AI Operations & Reliability
Maintenance and evolution of AI systems in production. Model drift monitoring, continuous fine-tuning, inference cost control, and observability. For systems that need to keep generating value after delivery.
Start small . Scale when value is proven.
Three formats. Same discipline of discovery, build, and handoff. You choose by duration and by the level of risk you accept at the entry.
PoC
Entry point to validate a hypothesis with success criteria and a production roadmap combined in the contract. Free PoC only in strategic cases.
Project
Closed scope, fixed fee, final delivery in production. Bi-weekly milestones with functional demonstration.
Allocated Squad
Levver team embedded with the client on a discovery + delivery cadence. Cancellable with prior notice.
Examples in local currency. Contract closed in BRL or USD.
From diagnosis to production , in three steps.
Every engagement, regardless of format, follows the same design. The difference between PoC, Project, and Squad is the size of each block, not the structure.
Diagnosis
1 to 2 weeks
We map the real pain, validate the technology hypothesis, and define measurable success criteria. We deliver an architecture document, target metrics, and an explicit production criterion.
Build
4 weeks to 6 months
System construction with a weekly or bi-weekly demonstration cadence. Code review shared with the internal team. Progressive deployment from staging to controlled production and full production.
Production & Handoff
1 to 2 weeks
Metric observed for at least two weeks in real production. Operations runbook, technical documentation, and knowledge transfer sessions. Optional post-handoff support of 3 to 6 months.
Frontier + open-source. No religion about stack.
The right model for the right problem. Claude, GPT, Gemini, Llama, Mistral, our own fine-tuned models. Patterns applied as needed. RAG, supervised fine-tuning, multi-step agents, MLOps, evaluation pipelines.
Primary infra on Google Cloud Platform. AWS on demand when the client is already there. Data isolated by client, zero training on sensitive data. Contractual clause.
- Frontier and open-source models
- RAG (Retrieval-Augmented Generation)
- Supervised fine-tuning
- Multi-step agents and tool use
- Vector databases (Pinecone, Weaviate, pgvector)
- MLOps and observability
- Automated evaluation (LLM-as-judge, eval datasets)
- Document ingestion and processing pipelines
- Python and TypeScript backend
- Next.js + React frontend
Delta and Maya run with real clients. Not in demo.
Levver’s own products are the living proof of technical capability. Before becoming products, they were problems solved for specific clients, chosen to scale as a vertical.
Delta
Extracts, classifies, and structures data from complex financial PDF reports directly into the client’s database. Replaces weekly hours of junior analysts.
Maya
Intelligent mentor for C-Levels and founders. 68 management levers, available 24/7, with the company’s context loaded.
Questions that come up before the first meeting .
Do you deliver the source code?
Yes. All code built stays in the client’s repository, with IP transferred in full at the end of the project. No black box, no dependency on a Levver proprietary platform.
Who is the technical owner during the project?
Always someone senior from Levver. Engineer or tech lead with direct presence. We don’t allocate junior staff in mass or use a relationship manager as an intermediary.
How does the handoff to the internal team work?
Technical documentation, operations runbook, knowledge transfer sessions, and optional post-handoff support (3 to 6 months). The goal is for your team to be able to operate and evolve the system without permanent dependence on Levver.
Can I hire a PoC to validate before closing a project?
Yes, that's Format 01. PoC with a fixed fee (USD 0 to 10k, up to 8 weeks), with success criteria and a production roadmap combined in the contract. Free PoC only in strategic cases.
How do you handle sensitive data?
Data isolated by client, encryption in transit and at rest, no training on client data (contractual commitment). LGPD and GDPR compliance.
What stack do you work with?
Frontier (Claude, GPT, Gemini) and open-source (Llama, Mistral) as appropriate. Python and TypeScript backend. Primary cloud GCP, AWS on demand. No stack religion.
How long until the first delivery?
Diagnosis in 1 to 2 weeks. Build between 4 weeks and 6 months, depending on scope. First metric observed in real production: on average 6 to 12 weeks from kickoff.
Do you serve outside Brazil?
Yes, in English or Spanish. Contracts in BRL, USD, or EUR. Most engagements today are in Brazil, but the team serves LATAM and English-speaking markets.
Founded by specialists who deliver.
Levver was founded in 2025 on the thesis that most companies have AI in an experimental phase, and almost none in production. Founders present throughout the strategic cycle of the project, with the purpose of turning experiment into result.
João Prado
2× founder with a proven track record of scaling operations from zero to exit. Specialist in turning operational bottlenecks into real cost and productivity efficiency, with a business model that sustains growth.
LinkedIn →Daniel Guilger
AI architect with experience in complex machine learning projects and high-precision processing for large industries and critical sectors. Builds systems that execute, not just recommend.
LinkedIn →Your next meeting is your diagnosis .
Thirty minutes with one of the founders. No deck, no committee. We leave the conversation with a prioritized AI hypothesis and a sketched success criterion.
contato@levver.ai · +55 11 9 6344 9882 · levver.ai/contact
Schedule diagnosis