Allogic is a boutique AI engineering consultancy based in Brazil, specialized in bespoke intelligent systems for healthcare, insurance, legal, and complex operations. We build predictive models, natural language processing (NLP), computer vision, and intelligent automation. Architecture can combine third-party models with client data and integrations. Projects start at BRL 60,000, with an initial estimate of 3 to 6 months, subject to diagnosis and scope.
We design AI systems for specific processes, with validation criteria, integrations, and operating responsibilities defined for the project. Book a 15-min consultation
What we define in a bespoke AI project
| Decision | Evaluation criteria |
|---|---|
| Models and APIs | Compare alternatives using representative examples, cost, and operating requirements |
| Data use | Assess whether the task calls for document retrieval, model tuning, or training |
| Intellectual property | Define client deliverables and identify third-party licenses and dependencies |
| Privacy | Document processing, access, retention, and provider involvement |
What AI engineering actually looks like
Applying artificial intelligence to a process requires understanding the business problem, evaluating existing tools, and defining how results will be measured before development.
At Allogic, every AI project starts with a direct question: how much is this problem costing you today? If the answer justifies the investment, we build a bespoke intelligent system. If it doesn’t, we say so clearly — and we suggest alternatives.
That is what a boutique AI consultancy is: strong technical opinions, few clients, deep projects.
What we build
Predictive models trained on your proprietary data
We assess operational data and test models suited to the problem. Selection depends on data quality and measured validation performance. Applications: demand forecasting, anomaly detection, risk scoring, opportunity prioritization.
Natural Language Processing (NLP)
Structured-information extraction from unstructured text: contracts, medical records, legal documents, emails, forms. We define quality metrics per task and routes for human review when confidence or risk requires it.
Computer Vision for inspection and recognition
Visual-pattern identification in images and video: document recognition, quality inspection, reading of scanned physical forms. Integrated directly into your process — not a lab demo.
Intelligent process automation
We combine business rules and AI to classify information and route tasks. Limits on automated action, exception handling, and human review are defined according to process risk.
AI diagnosis and roadmap
For organizations that don’t know where to start: we map processes, evaluate available data, identify where AI generates real ROI, and deliver a technical execution plan with investment and return estimates.
How a bespoke AI project works
A typical AI engineering project at Allogic has four phases:
1. Problem diagnosis (1–2 weeks) We understand the current process, map available data, and validate technical and economic feasibility. You get an honest assessment — including “not worth it right now” when that’s the truth.
2. Intelligent system architecture (1–2 weeks) We define the technical architecture: which models, which training data, how to integrate with your existing systems, how to monitor in production. A detailed proposal with phases, timeline, and projected ROI.
3. Build and validation (6–16 weeks) Short delivery cycles. You validate each component before moving forward. Tests inform scope adjustments and acceptance criteria.
4. Production and ongoing support Deploy in the environment defined for the project. Quality monitoring, model updates, and support depend on the architecture and contracted operating scope.
How we select models and providers
Our technology partnership approach includes models from OpenAI, Anthropic, and Google, open models, or models trained for the task. RAG, fine-tuning, and training are alternatives evaluated during diagnosis; none provides superior accuracy by definition.
Code developed specifically for the project is delivered under the contract. Third-party models, libraries, and APIs retain their own licenses and terms. The proposal should identify those dependencies, recurring costs, and continuity options.
Sectors where we apply AI
- Healthcare and hospitals: medical-record processing, automated triage, exam analysis, privacy by design
- Insurance and brokerages: risk scoring, claims analysis, underwriting automation
- Legal and compliance: contract reading, clause extraction, obligation monitoring
- Operations and logistics: demand forecasting, anomaly detection, route optimization
Investment
Bespoke AI projects at Allogic start at BRL 60,000, with typical timelines of 3 to 6 months depending on complexity. We charge for value delivered, not hours logged — aligning our incentives with the client’s outcome.
The initial conversation is free and without commitment. The 15-minute conversation helps us understand the problem and suggest next steps; feasibility requires diagnosis.
Frequently Asked Questions
Can bespoke AI use third-party models and APIs?
Yes. A system can combine third-party models, RAG, model tuning, or models trained on the client’s data. Architecture is selected during diagnosis and evaluated with representative examples. The contract defines ownership of deliverables; third-party components retain their own licenses.
How is project data handled?
Diagnosis identifies the data used, where it is processed, and which providers have access. Access controls, retention, and privacy requirements are defined for the project. External APIs depend on assessment of the data, contracts, and client requirements; architecture alone does not guarantee regulatory compliance.
What is the investment required for a bespoke AI project?
Bespoke projects start at BRL 60,000, depending on data complexity and model architecture. Scope, deliverables, and operating costs such as cloud and APIs should be specified in the proposal.