AI systems and custom AI employees
Determinds builds AI systems and custom AI employees that take on repeated work in human resources, accounting, sales, and marketing, alongside document intelligence, retrieval-augmented search, operational copilots, and matching engines. Our team has delivered 8+ GenAI projects across banking, procurement, policy research, real estate, and marketing, each designed with its orchestration and failure handling in place before launch.
01 AI capabilities
AI systems built around your business logic
Determinds engineers AI systems around a client’s own business logic, covering natural language processing, machine learning, and workflow automation, and builds each one on a custom backend so it can reach whatever else the client runs.
Workflow automation
Repeated back-office steps handed to models that follow your own business rules, with a human checkpoint at every step where accuracy matters most.
AI workflow automation servicesConversational assistants
Assistants that hold context across a conversation and connect to the platforms and APIs you already use, so every support request reaches a system that can resolve it.
Matching engines
Weighted matching that connects requests with suppliers and clients with services, in real estate, procurement, and healthcare, with the reasoning behind each match visible.
CRM and form automation
Data entry, form filling, and record updates carried out inside the CRM and workflow tools your team already uses, drawn from your own records.
Knowledge extraction
Entities, relationships, and patterns extracted from meeting transcripts, email, audio, and video, and organized into a structure your team can search and query.
Document intelligence
Arabic and English OCR on unstructured documents, with fields validated against your business rules and uncertain results routed to a reviewer.
Read the case study02 Matching engines
Every match ranked, with the reasoning visible
Our matching engines score each candidate against weighted criteria, so a broker, a buyer, or a procurement team sees the ranking and the trade-off behind every result.
Ranked shortlist
IllustrativeRequest: Replace a manual vendor onboarding process across three business units
| Firm | Match strength | Why it ranked |
|---|---|---|
| Firm AProcess consulting | Closest sector experience, available in the required window | |
| Firm BSystems integration | Strong delivery record, with a later start date | |
| Firm CChange management | Partial fit, covering the people side of the change only |
03 Conversational assistants
Answers drawn from your own documents, with every source cited
Our assistants retrieve the passages that answer a question, reply in Arabic or English, and cite the policy and clause behind each answer, so your team can verify it in one click.
Policy assistant
Illustrativeما حدود صلاحية مدير الفرع للموافقة على تسهيل غير مضمون لشركة صغيرة؟
يوافق مدير الفرع على التسهيلات غير المضمونة للشركات الصغيرة في حدود صلاحياته الواردة في سياسة الائتمان، ويرفع ما يتجاوزها إلى لجنة الائتمان الإقليمية.
- سياسة الائتمان · البند ٤٫٢
Which approvals does a facility above the branch limit need?
It goes to the regional credit committee, with the documents listed in the Credit Policy.
- Credit Policy · Section 4.3
04 Regulated industries
AI systems for regulated industries
Banking and payments
Fraud signals, risk assessment, and customer insight built on the transaction data a bank already holds, and delivered through the bank’s own information security review.
Healthcare
Patient-data analysis and operational tooling built to HIPAA standards, with data boundaries drawn before any model or framework is chosen.
Enterprise operations
Platforms that bring AI to sales, marketing, operations, and customer service on one data model, so every team works from the same records.
05 Deployment
Models that run inside your environment
Determinds deploys models through the provider APIs you approve or as self-hosted models inside your own infrastructure, so prompts, documents, and customer records stay within the boundary your obligations set.
Your environment, on premise or private cloud
Document intelligence
Arabic and English OCR
Assistants
Answers with their sources
Matching engines
Weighted, explainable ranking
Workflow automation
Steps handed to models, with checkpoints
A model layer, built and maintained by Determinds
Self-hosted or approved provider models · retrieval over your documents · human checkpoints · audit trail
Your existing systems
ERP
CRM
Document archives
Data warehouse
06 How we deliver
From your current process to a model in production
Process and data review
Our team maps your current process and audits the data behind it, whether that is spreadsheets, CRM records, PDFs, transaction logs, or raw text, and works with your data in whatever state it is today.
Scope and measures
Together we scope the problem and agree on the measures it will be judged on, such as processing time, prediction accuracy, or cost per automated task, and sign them off before development starts.
Build and integrate
Models run as modular services behind APIs, webhooks, or direct database access, so your legacy ERP, SaaS stack, and internal tools all connect without being rebuilt.
Monitor and retrain
Dashboards track model performance in production, and scheduled reviews retrain or tune the system as your data changes.
07 Technology
Tools chosen for each engagement
Every tool is selected against your requirements for security, cost, latency, scale, and governance, and the choice is made afresh on every engagement.
- Models
- OpenAI, Claude, Gemini, Llama, Mistral
- AI frameworks
- LangChain, Mastra, CopilotKit, custom orchestration
- Vector stores
- Pinecone, PGVector
- Backend
- NestJS, Java, Python
- Infrastructure
- AWS, GCP, on-premise, Docker, Kubernetes
08 Frequently asked
Questions about custom AI systems
What is the difference between custom AI and an off-the-shelf AI tool?
A custom AI system from Determinds is engineered around your own data, workflows, and objectives, while an off-the-shelf tool is built for the general case. A custom system follows your business logic, connects to the infrastructure you already have, and improves on your real operations rather than on generic training data.
How long does a custom AI system take to build?
Determinds typically delivers a first production release 8 weeks after kickoff, with requirements reaching scope sign-off in 5 working days. Our team works in 2-week sprints with a demo at the end of each, so you see progress from the first sprint.
What data is needed to start?
Determinds starts from the data you already have. Our team audits your spreadsheets, CRM records, PDFs, transaction logs, and raw text, then designs the pipeline that prepares it for training. Where volumes are still low, transfer learning or synthetic data supports development while your own data grows.
How does an AI system connect to the systems already in place?
Determinds builds each AI system as a modular service reached through APIs, webhooks, or direct database integration, whether you run a legacy ERP, a modern SaaS stack, or internal tools. Every integration is documented and handed over with full API specifications.
How is success measured?
Determinds measures success against goals agreed before development starts and tied to your objectives, such as processing time, prediction accuracy, cost per automated task, or lead qualification rate. Monitoring dashboards track the model in production, and scheduled reviews retrain it as your data evolves.
AI systems
AI systems that take on your team’s repeated work
Your first conversation is with a Determinds engineer, who identifies the manual work where AI will deliver value first.