My team is stuck with repetitive work
Leads, approvals, CRM, finance, inboxes and scattered tasks that should flow safely between tools.
ALPER ZAKHER
Alper Zakher — Senior AI Automation Engineer & Agentic AI Developer
I design and build AI agents, business automation systems, LLM-powered products, internal tools, RAG systems and AI-integrated applications for companies.

You don’t need to choose a model or tool first. Pick your challenge and explore an example of the engineering behind a practical solution.
Leads, approvals, CRM, finance, inboxes and scattered tasks that should flow safely between tools.
Build useful, source-grounded assistants for internal knowledge, documents or customer support.
A real app with governed agents, integrations, user roles, data and a production-ready experience.
Choose a business challenge, then click the architecture nodes to explore how information moves through checks, AI, human approval and controlled delivery.
Accept a lead from an approved channel with a traceable request ID.
Public repositories sync automatically from GitHub. Each card links directly to its source. Open-source implementations are engineering evidence, not invented client results or unverified performance claims.
MCP tools to composed agent workflows
Request to best model/provider
Arbitrary financial docs to schema-mapped JSON
Supplier thread to structured PO/procurement data
MCP tools to Shopify store operations
LLM usage to metering and billing
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From AI agents, CRM and data engineering to voice, vision, RAG, evaluation and model infrastructure: explore 24 concrete capabilities across eight disciplines. Each entry explains the business problem, engineering approach and safety constraints—not unverified promises.
Fragmented leads, slow qualification and duplicated follow-up.
Explore architecture & details ↗Fragmented leads, slow qualification and duplicated follow-up.
Capture consented enquiries, deduplicate, enrich approved fields, qualify intent and route ownership across CRM and messaging.
Consent, API scopes, deduplication, manual escalation and audit trail.
Invoices, receipts and reconciliations consume repetitive manual effort.
Explore architecture & details ↗Invoices, receipts and reconciliations consume repetitive manual effort.
Extract fields, check totals and tax rules, match purchase orders, flag exceptions and create reviewed accounting drafts.
Never post payments or journal entries without authorized validation.
Purchase requests and supplier updates become difficult to trace.
Explore architecture & details ↗Purchase requests and supplier updates become difficult to trace.
Route requests, parse supplier emails, compare approved quotations, check inventory thresholds and issue tracked purchase workflows.
Vendor decisions require defined sourcing rules and human approval.
A model can answer questions but cannot safely perform bounded operations alone.
Explore architecture & details ↗A model can answer questions but cannot safely perform bounded operations alone.
Design agents with typed tools, task limits, retries, stop conditions and verifiable outcomes.
Least privilege, action confirmation, prompt-injection defenses and logging.
Specialized research, planning, verification and execution steps need coordination.
Explore architecture & details ↗Specialized research, planning, verification and execution steps need coordination.
Separate planning, retrieval, execution and critique with explicit inputs, outputs, ownership and recovery paths.
Limit loops, budgets and delegation depth; require human control for consequential actions.
Teams repeatedly interact with interfaces that lack a usable API.
Explore architecture & details ↗Teams repeatedly interact with interfaces that lack a usable API.
Automate permitted UI workflows with visual state checks, exception handling and supervised handoff.
Honor service terms, user authorization, session security and verification before submit.
Company answers are scattered across PDFs, policies and internal portals.
Explore architecture & details ↗Company answers are scattered across PDFs, policies and internal portals.
Ingest approved documents, chunk, index, retrieve, rerank and answer with citations.
Filter by access rights before retrieval and abstain when evidence is weak.
Employees lose time finding current, authoritative information.
Explore architecture & details ↗Employees lose time finding current, authoritative information.
Federate permitted sources, rank freshness and relevance, show provenance and index changes.
Respect tenant boundaries, retention rules and source-of-truth ownership.
Outdated FAQs and tribal knowledge undermine AI reliability.
Explore architecture & details ↗Outdated FAQs and tribal knowledge undermine AI reliability.
Extract candidate knowledge, route editorial review, version articles and evaluate assistant answers.
Publication approval, citations, freshness checks and redaction.
Operational data is fragmented across CRMs, spreadsheets and databases.
Explore architecture & details ↗Operational data is fragmented across CRMs, spreadsheets and databases.
Build event pipelines, normalization, validation, deduplication, warehouse models and monitoring.
Schema contracts, PII minimization and failure replay.
Leaders need reliable operational views rather than static reports.
Explore architecture & details ↗Leaders need reliable operational views rather than static reports.
Model KPIs, consolidate approved sources, automate reporting and surface drill-down views.
Document metric definitions and avoid unsupported attribution.
Unexpected demand or system deviations can remain invisible until late.
Explore architecture & details ↗Unexpected demand or system deviations can remain invisible until late.
Detect unusual patterns, estimate plausible scenarios and alert operators with confidence and context.
Validate against holdout data, monitor drift and keep human decisions.
Customer context is lost between chat, email, helpdesk and voice.
Explore architecture & details ↗Customer context is lost between chat, email, helpdesk and voice.
Classify and route conversations, draft grounded answers, maintain tickets and escalate complex cases.
Consent, escalation, identity verification and safe refusal.
Pipeline signals and follow-up actions often go unprioritized.
Explore architecture & details ↗Pipeline signals and follow-up actions often go unprioritized.
Summarize approved meeting notes, identify next steps, flag stale opportunities and draft reviewed follow-ups.
Respect communication preferences, consent and anti-spam rules.
Campaign operations demand coordination across content, creative and measurement.
Explore architecture & details ↗Campaign operations demand coordination across content, creative and measurement.
Plan content, manage approval workflows, unify campaign reporting and personalize authorized segments.
Brand approval, privacy controls and platform policy compliance.
Forms and contracts arrive as inconsistent formats and manual scans.
Explore architecture & details ↗Forms and contracts arrive as inconsistent formats and manual scans.
Classify pages, extract fields, validate schemas, highlight uncertainty and create reviewer queues.
Redact sensitive fields and require approval for consequential documents.
Calls, multilingual voice notes and appointment requests are hard to structure.
Explore architecture & details ↗Calls, multilingual voice notes and appointment requests are hard to structure.
Transcribe permitted audio, identify intent, route requests and design voice assistants with handoff.
Disclosure, recording consent, accent testing and secure retention.
Image and video assets need classification, quality checks and structured metadata.
Explore architecture & details ↗Image and video assets need classification, quality checks and structured metadata.
Build permitted image/video analysis, asset tagging, moderation, captioning and review pipelines.
Human review for sensitive inference, rights clearance and bias checks.
A chatbot alone is rarely a complete business product.
Explore architecture & details ↗A chatbot alone is rarely a complete business product.
Build dashboards, review queues, user roles, APIs, durable databases and production UX around AI.
Authentication, authorization, audit logs and graceful failure states.
Applications and agent tools require consistent service contracts.
Explore architecture & details ↗Applications and agent tools require consistent service contracts.
Build typed REST/GraphQL/MCP connectors, webhooks, queues, idempotent endpoints and observability.
Token scopes, secrets vault, rate limits and rollback design.
Models have different capabilities, costs, privacy rules and latency.
Explore architecture & details ↗Models have different capabilities, costs, privacy rules and latency.
Use policy-based routing, fallbacks, budgets, caching, prompt versions and evaluation gates.
Data residency, prompt safety, provider terms and cost caps.
Promising demos can silently fail on real workloads.
Explore architecture & details ↗Promising demos can silently fail on real workloads.
Define success criteria, test datasets, groundedness metrics, traces, alerts and regression tests.
Avoid fabricated benchmarks; report uncertainty and incident pathways.
Not all AI decisions should execute autonomously.
Explore architecture & details ↗Not all AI decisions should execute autonomously.
Build approval queues, role-based checkpoints, exception paths, reversals and operator tooling.
Separation of duties, authorization and nonrepudiation.
AI integrations can expose sensitive information or unsafe tools.
Explore architecture & details ↗AI integrations can expose sensitive information or unsafe tools.
Threat-model workflows, enforce tenant isolation, redact PII, secure credentials and monitor abuse.
Least privilege, retention/deletion policies and red-team testing.
No matching capabilities. Try another search or category.
A useful AI system needs the complete engineering foundation—not just a model or prompt.
Map users, workflows, data boundaries and measurable outcomes.
Prepare approved sources, quality checks, retention and access rules.
Choose models, retrieval, tools and integration patterns.
Add validation, approvals, failure recovery and execution limits.
Build usable interfaces, explanations and error-handling paths.
Test outcomes, monitor quality, cost, security and reliability.
Alper Zakher designs AI agents, business automation systems, RAG systems, internal tools and AI-integrated applications from Cairo for companies in Egypt, Saudi Arabia, the GCC and internationally.
AI agents that act through approved tools; workflow automations that connect business systems; RAG and document systems grounded in company knowledge; and production-minded internal tools and AI products.
Lead qualification, CRM handoffs, document extraction, support triage, internal knowledge retrieval, reporting, approvals and operational alerts can be mapped into controlled, reviewable workflows.
Connect triggers, APIs, rules, data stores, approvals and reporting. Deterministic workflow logic stays in control while models handle bounded interpretation, extraction, drafting or classification.
Build tool-using agents with scoped permissions, retrieval, structured outputs, approval gates, audit trails, stop conditions and human escalation.
Create the product and data layers around AI: RAG, document pipelines, internal tools, APIs, model routing, evaluation and observability.
Evidence-led notes explain the problem, constraints, architecture, implementation and available public proof. Results remain qualitative whenever a defensible benchmark is unavailable.
View case studies ↗MCP Composer, Model Router, Universal Document Parser, Invoice AI, Supplier Email Parser and developer tools demonstrate concrete system patterns without being presented as client engagements.
Explore the portfolio ↗Discovery maps the workflow. Scope defines users, data, permissions and success. Build starts with the smallest useful path, followed by evaluation, staged release, monitoring and iteration.
Alper Zakher is the professional name of Alper Nabil Gabra Zakher, a Cairo-based Senior AI Automation Engineer, Agentic AI Developer and AI Systems Builder.
Yes. Alper supports Saudi and GCC companies remotely from Cairo and does not claim a physical Saudi office.
Yes. Work can include APIs, CRMs, WhatsApp-enabled workflows, databases, document pipelines and internal tools, subject to provider access and security requirements.
No technology shopping list up front. First we map the workflow, data, permissions and evidence of value—then decide what is actually worth building.
Understand the people, bottlenecks, outcomes and systems involved.
Define a practical scope, data sources, integrations, approval gates and risks.
Build a focused path, test with approved data and review failures before expansion.
Release with permissions, logs and monitoring; iterate from observed evidence.
Timing, pricing and delivery depend on system complexity, data access and integration scope. We define those before making commitments.
Book a discovery conversation ↗Bring the business challenge, the constraints and the goal. We’ll explore the smallest useful system, with safeguards and a clear next step.