AI Engineering

Bespoke Artificial Intelligence: Intelligent Systems for Enterprise

Is your business losing time to manual workflows? We design and build predictive models, OCR, and custom intelligent automations. Book a diagnosis!

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, NLP, Computer Vision, and intelligent automation trained on the client’s proprietary data. Projects start at R$ 60,000, typical delivery in 3 to 6 months, with source code and models owned by the client.

BLUF (Bottom Line Up Front): True AI engineering goes beyond writing simple prompts. We design and integrate predictive models and NLP systems within your company’s own cloud infrastructure, ensuring full intellectual property (IP) ownership and strict data security. Book a 15-min consultation

Comparative Table: Bespoke AI (Allogic) vs. Generic AI APIs

AspectBespoke AI (Allogic)Generic AI APIs
Training DataYour proprietary, exclusive dataPublic data from third parties
Accuracy & DomainOptimized for your industry’s jargonLower accuracy on specific domain terms
Intellectual PropertyModel and code belong to your companySubscription access (no IP control)
Data SecurityFull isolation in your own cloudConfidential data sent to external servers

What AI engineering actually looks like

Artificial Intelligence is not a product you buy off the shelf. It is an engineering discipline that requires understanding the business problem before writing a single line of code.

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

Models trained exclusively on your operational data — not generic models retrofitted. The result is superior accuracy and a data asset that stays with the client. 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. Our intelligent systems read, classify, and route documents with accuracy above 90% — no human in the default flow.

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

Unlike classic RPA, our AI-driven automations make decisions: they understand context, handle exceptions, and learn from the history of operations. The result: processes that used to require human analysts now run with minimal supervision.

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. No surprises at the end.

4. Production and ongoing support Deploy in the client’s environment or on a managed cloud. Model-drift monitoring, periodic retraining, and direct technical support from the people who built the system.


Why not a generic AI model?

Generic models — such as off-the-shelf AI APIs — are powerful for standard use cases. But when your problem has domain-specific particulars (medical terminology, legal jargon, proprietary operational data), generic models deliver mediocre results.

A bespoke intelligent system is trained on your data, speaks the language of your industry, and is optimized for your use case. The source code and the models are the client’s assets — no dependency on an external vendor.


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 around USD 12,000, 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. In 15 minutes, you’ll know whether AI fits your problem right now.

Frequently Asked Questions

What is the difference between bespoke AI and generic APIs?

Generic APIs like OpenAI’s are great for general tasks but fail on domain-specific terms (such as medical records or insurance jargon). Bespoke AI is trained on your exclusive data, ensuring superior accuracy and full IP ownership.

How do you ensure data security and compliance (GDPR/LGPD)?

Allogic builds systems with privacy by design. The model and database run isolated within your company’s own cloud environment (AWS, GCP, or Azure), ensuring no sensitive data is shared with third parties.

What is the investment required for a bespoke AI project?

Bespoke projects start around USD 12,000, depending on data complexity and model architecture. Payment is structured around milestones, with no hidden fees.