Amazon Web Services
Building agentic systems on AWS—production-style wiring across services, security boundaries, and scalable runtimes.
Intelligent systems for what comes next.
Official FlutterFlow Expert. I finish stalled apps, harden vibe-coded builds from Lovable, Bolt, and Cursor, and ship production agents. Start with a 30-minute call — no account required.
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AI ServicesNew
Start with autonomous research
Run a cited audit or a full marketing playbook — one complimentary run per email, with live agent progress and optional Pro for unlimited runs.
ImadDhin Agentic System
Agentic Production
A personal agentic platform in active build—trusted agents, clear surfaces, and workflows you can run in production, not just demos. Shipping with leading SDKs and tools across AWS, Google's AI agent stack, Chatbase, and Agent.so for grounded, client-ready experiences.
Built with leading SDKs & tools
Google AI Agent Platform
Gemini-class models and agent SDKs for structured tools, safe execution, and clear evaluation in live products.
- CChatbase
Chatbase
Agent-ready support surfaces and knowledge-grounded replies—compose into broader agentic workflows.
Agent.so
Your portal to AI®
Trainable agents, shared chat surfaces, and a product vocabulary aligned with how people actually ship AI companions—not one-off demos.
Brand system per Agent.so brand.
Vibe-Code Rescue & Production Hardening
It works in the demo.
Then real users arrive.
AI tools ship a prototype in a weekend — then it breaks the week it gets traction. Auth has holes, secrets leak into the bundle, payments aren't idempotent, and every AI fix breaks something else. I take apps from Lovable, Bolt, Cursor, v0, Replit, and FlutterFlow and make them production-grade — the auth, payments, security, and architecture the AI skipped. You keep your code and your stack.
~45% of AI-generated code ships an OWASP Top 10 flaw2.74× the human security-bug rate
Build fast → cracks under real users → hardened to production-grade.
Products
Spec-first scope, typed and tested delivery, evals before launch, and observability built in — every line ships production-ready.
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Mirra Network
Dark, location-aware social networking app with Digital Personas — AI chat proxies for people. Figma-driven glass UI, ready to extend into production.
(1) Design system — black base, matte surfaces, frosted glass, MIRRA lime accent, shared type/radius/spacing tokens. (2) Navigation — Expo Router stack with fade transitions and a floating glass dock (Profile · Network · DM · Chats · Search). (3) Network feed — people discovery cards with location, interests, Connect/DM, Card/Map segment. (4) Profile & messaging — hero stats, Train AI Chat UI, DM inbox with Direct / Digital Persona filters. (5) Handoff — mock data layer ready to swap for auth, live feed, chat, maps, push, and store packaging.
$20
/01
AI Integration & Infrastructure
LLMs, vector stores and pipelines wired into your product — infrastructure that holds up in production.
(1) Audit — map use cases, data and a cost ceiling per request. (2) Architecture — RAG/cache/queue design with latency and failover plans. (3) Integration build — API and pipeline code plus the prompt/context layer. (4) Validation — eval suite, load tests, cost-per-request checks. (5) Ship & monitor — tracing, alerts, iteration on real traffic.
Custom quote
/02
RAG Chatbots & Machine Learning
Chatbots grounded in your data — retrieval done right so answers stay true.
(1) Data audit — source inventory, cleaning, chunking strategy. (2) Retrieval design — embedding/index choice, hybrid search + reranking. (3) Build — pipeline and chat orchestration with citations and memory. (4) Eval harness — groundedness and recall sets, hallucination gates. (5) Launch — feedback loop and continuous index updates.
Custom quote
/03
MCP Server Development
Custom MCP servers that connect Claude and any LLM to your tools, data and APIs — typed, tested, deployed.
(1) Tool surface — choose the right tools to expose with sane naming and granularity. (2) Schema design — typed params/results, auth and transport spec. (3) Server build — MCP SDK implementation with resources and prompts. (4) Agent testing — Claude-in-the-loop runs against edge and error paths. (5) Publish — versioned releases, registry listing, docs.
Custom quote
/04
AI Automations
Hands-off workflows that read, decide and act — your ops on autopilot, with guardrails.
(1) Process map — inventory manual steps, rank by ROI. (2) Flow design — triggers, branches, human-approval points. (3) Build — scenarios with AI steps and clean data mapping. (4) Guardrails — error paths, retries, cost and rate limits. (5) Handover — runbook, alerts, monthly tune-up option.
Custom quote
/05
Custom Multi-Agent Systems
Orchestrated agents that reason, plan and act together — built to ship.
(1) Decomposition — split the goal into agent roles and handoffs. (2) Orchestration — LangGraph state design, supervisor vs swarm choice. (3) Agent build — tools, memory and structured outputs per agent. (4) Evals & tracing — task-success metrics with full-run traces. (5) Production — deploy, autoscale, cost and drift monitoring.
Custom quote
/06
Custom AI Integration — MCP + LLM
Drop AI into your existing product — MCP-powered, with the model that fits your use case.
(1) Model fit — benchmark 2–3 models on your task for price/latency. (2) Bridge design — MCP server into your stack with a permissions model. (3) Integration — feature build inside your product with streaming UX. (4) Safety & cost — guardrails, budgets, fallback chains. (5) Launch — usage analytics and prompt iteration.
Custom quote
/07
Build Your Custom AI Agent
One agent, your tools, your rules — scoped, built and shipped on AWS.
(1) Scope — a single job-to-be-done with explicit success criteria. (2) Design — tool and memory schema, prompt architecture. (3) Build — agent loop on AWS with tool integrations. (4) Test — task battery runs, failure recovery. (5) Deploy — serverless with logs and weekly iteration.
Custom quote
/08
Ship Your Next Application
From spec to store — full application development with the leading cross-platform stack.
(1) Product spec — features, user stories, scope freeze. (2) UX flows — wireframes, design system, clickable prototype. (3) Build sprints — weekly shippable builds with backend and auth. (4) Device QA — real-device matrix, crash and performance pass. (5) Store launch — ASO, listing assets, phased rollout.
Custom quote
/09
Next.js Web App + AI SDK
Modern web apps with AI built in — streaming UI, server actions and edge-fast deploys on Vercel.
(1) Spec — pages, data model, AI feature definition. (2) Architecture — App Router and RSC plan, auth and DB choice. (3) Build — UI, server actions, AI SDK streaming. (4) Hardening — performance, SEO, accessibility to Lighthouse 95+. (5) Deploy — Vercel with analytics and preview-driven iteration.
Custom quote
/10
End-to-End WordPress Website
Custom WordPress, designed and shipped end to end — fast, editable and built to convert.
(1) Content map — pages, conversion goals, sitemap. (2) Design system — brand, components, mobile-first comps. (3) Theme build — custom blocks and ACF for an editor-friendly CMS. (4) Speed & SEO — Core Web Vitals, schema, meta. (5) Launch — training video and optional care plan.
Custom quote
/11
Streamlined Mobile / Web App Development
A senior builder on your project every week — mobile and web shipped in continuous sprints.
(1) Intake — backlog and priorities, week-1 plan. (2) Sprint plan — scoped weekly goals with demo checkpoints. (3) Build — ship every week with async Loom updates. (4) Review — feedback folded in, next sprint scoped. (5) Repeat — velocity tracked; pause or scale anytime.
Custom quote
/12
Build Your Modern Web App
From wireframe to deployed product — modern stack, clean design, measurable performance.
(1) Spec — user flows and data model agreed. (2) UI system — Tailwind components on a responsive grid. (3) Build — frontend plus Supabase auth and RLS. (4) Quality — tests, Lighthouse 95+, cross-browser pass. (5) Deploy — CI/CD, monitoring, handover docs.
Custom quote
/13
App Development as MVP Product
Your idea as a real, testable product — scoped tight, built fast, ready for first users.
(1) Scope cut — core loop only, 2–3 week plan. (2) Flows — clickable prototype for fast validation. (3) Core build — must-have features with analytics events. (4) Beta — TestFlight/internal testing with real users. (5) Launch — store release, metrics review, next bets.
Custom quote
/14
Build Your Own Backend Model
Backends that scale with you — data models, APIs and cloud infrastructure done right.
(1) Domain model — entities, relations, access patterns. (2) API contract — endpoints, types, versioning plan. (3) Build — DB, API, auth, migrations. (4) Hardening — load and security tests, backup/recovery. (5) Deploy — IaC, CI/CD, runbook and docs.
Custom quote
/15
AI Application Development
Full applications with AI at the core — chat, vision, voice and automation as product features.
(1) Concept — AI feature-market fit, model selection. (2) Product design — UX around AI moments with a latency budget. (3) Full-stack build — app plus AI backend, streaming and caching. (4) AI QA — evals, abuse cases, cost ceilings. (5) Launch — usage analytics, prompt and model iteration.
Custom quote
/16
Flutter Application Development
Native-feel apps for both stores from one codebase.
(1) Spec — screens, integrations, estimate. (2) Design system — theming, components, motion language. (3) Build — feature sprints with state management and offline support. (4) Device QA — iOS + Android matrix, performance profiling. (5) Release — Fastlane pipelines, store + OTA updates.
Custom quote
/17
AI Engineering — Embedded
A senior AI engineer inside your team — architecture, reviews and shipping, every week.
(1) Onboard — codebase and infra audit, quick-wins list. (2) Roadmap — AI opportunities ranked into a quarterly plan. (3) Build cycles — weekly shipping cadence with pairing and reviews. (4) Quality — eval coverage grows, cost dashboards live. (5) Compound — your team upskilled; capability stays in-house.
$2,500–4,000/mo retainer
/18
Machine Learning & LLM Fine-Tuning
Custom models on your data — fine-tuned, evaluated and served at production latency.
(1) Data prep — collection, cleaning, train/eval splits. (2) Baseline — prompted baseline scores, eval set locked first. (3) Fine-tune — LoRA/QLoRA runs with hyperparameter sweeps. (4) Benchmark — against baseline and base model with regression checks. (5) Serve — quantize, deploy, monitor latency and drift.
From $3,000/project
/19
Vibe Coding Sprint
AI-assisted build sprints with Claude Code, Cursor and v0 — your idea live in front of users in days, not months.
(1) Day 0 scope — one core flow chosen, success demo defined. (2) AI scaffold — Claude Code generates the project base. (3) Iterate daily — build–review loops you watch live. (4) Harden — the core path made solid, real auth and data. (5) Demo day — deployed, shareable, next-step roadmap.
$1,500/sprint (1 week)
/20
Agentic Coding for Dev Teams
Install agentic coding in your org — pipelines, skills and guardrails that multiply your existing developers.
(1) Audit — current workflow, tools, friction inventory. (2) Setup — custom skills, MCP servers, repo conventions. (3) Guardrails — CI hooks, review gates, security policy. (4) Training — hands-on team sessions with playbooks. (5) Adoption — usage metrics and 30-day tuning.
$2,000/setup + training
/21
Voice AI Agents
Realtime voice agents that listen, reason and speak — call handling, coaching and support that never sleeps.
(1) Call flows — scripts, intents, escalation rules. (2) Voice stack — LiveKit plus a realtime model, voice selection. (3) Agent logic — tools, knowledge, interruption handling. (4) Latency tuning — sub-second turns validated on real calls. (5) Launch — telephony or in-app, transcripts and analytics.
From $3,000
/22
Computer Vision & Multimodal AI
Apps that see — document scanning, object recognition and multimodal pipelines, cloud or on-device.
(1) Sample data — real-world image set with edge cases listed. (2) Model select — cloud (Gemini) vs on-device (ML Kit) against accuracy targets. (3) Pipeline build — capture → infer → act with fallback paths. (4) Eval — precision/recall on the set, field-condition tests. (5) Ship — on-device optimization, telemetry, retraining loop.
From $2,500
/23
Web3 & Smart Contract dApps
Smart contracts and dApps shipped end to end — audited logic, clean UX, real users.
(1) Contract spec — token/logic design with a threat model. (2) Develop — Solidity with full test coverage and gas optimization. (3) Audit — static analysis, review, testnet battery. (4) dApp front-end — wallet UX, signing, clean onboarding. (5) Mainnet — deploy, verify, monitoring and ops.
From $4,000
/24
Fintech & Payments Systems
Stripe billing, subscriptions, paywalls and payout flows — built reliable, webhook-safe and compliance-aware.
(1) Money map — every flow from charge to payout, edge cases listed. (2) Architecture — Stripe object design with an idempotency plan. (3) Build — billing, paywalls, webhook-safe handlers. (4) Compliance pass — PCI scope, SCA, dunning, refunds. (5) Go-live — reconciliation reports, alerting on money paths.
From $2,000
/25
AI Security & Guardrails
Red-team your AI before someone else does — injection defense, guardrails and audit trails.
(1) Threat model — attack surface mapped to OWASP LLM Top 10. (2) Red-team — injection and jailbreak battery, data-exfiltration probes. (3) Guardrails — input/output filters, permission boundaries. (4) Harden — fixes with regression evals, audit logging. (5) Report — findings + fixes doc, retest, sign-off.
$1,500/audit
/26
Data Engineering & Knowledge Pipelines
From raw sources to AI-ready knowledge — ingestion, distillation and retrieval that scale.
(1) Source audit — systems, formats, freshness requirements. (2) Pipeline design — schema, flow plan, distillation strategy. (3) Build — ingest and transform, embedding and indexing. (4) Quality — dedup, drift checks, retrieval benchmarks. (5) Serve — APIs and retrieval layer with scaling and monitoring.
From $3,000
/27
Physical AI & Robotics
AI that moves things — vision-guided control, simulation and edge inference for real machines.
(1) Task spec — motion and sensor needs inside a safety envelope. (2) Simulation — digital twin setup, policy training. (3) Perception + control — vision and planning stack as ROS 2 nodes. (4) Sim-to-real — calibration, field tests, failure modes. (5) Edge deploy — Jetson optimization with remote telemetry.
From $4,000
Pricing
Project tiers
From rapid validation sprints to full-scale team engagements.
1 week
Discovery Sprint
from $2k
Scoping session, technical spec, and a priced estimate ready to share.
Start scoping →Popular
4–8 weeks
MVP / Launch
from $5k
Full-stack delivery — design, build, QA, and handoff for web, mobile, AI, or blockchain.
Start your MVP →Ongoing
Ongoing / Scale
from $10k
Retainers, sprints, and embedded engineering for longer-running or high-touch work.
Talk to us →Flexible
Custom
Custom pricing
Non-standard scope, phased roadmaps, or budget caps—we quote to fit after a short discovery.
Discuss scope →MVP builds from $5kFully remoteContra-verified
AI-native development
Built with the best AI tools
Hands-on with Cursor, Claude Code, Codex, and Antigravity for production-grade delivery.
Cursor
Cursor
Primary shipping cockpit for production implementation and review loops with deep codebase context.
- Repo-scale coding with agent + composer flows
- Inline, tab, and multi-file edits with context
- MCP-connected workflows for production velocity
- From planning to implementation in one surface
Claude Code
Anthropic
Reasoning-heavy execution for complex systems, delivery orchestration, and high-context coding sessions.
- Long-horizon coding tasks with strong reasoning
- Reliable tool-use and multi-step implementation
- Architecture-aware iteration and refactoring
- Production-grade agent patterns around Claude APIs
Codex
OpenAI
Execution-focused coding workflows for fast iteration, deep task automation, and production integration.
- Agentic coding and tool execution in production loops
- Fast code synthesis with iterative constraints
- Automation for implementation + validation tasks
- Model-driven acceleration across app and backend work
Antigravity
High-leverage async execution for broad implementation arcs and faster end-to-end delivery.
- Async coding sessions for long-running implementation
- Agent orchestration for multi-step engineering work
- Cloud-aligned development and review loops
- High-speed experimentation toward production readiness
Stack & platforms
Leading technologies used
Production delivery across web, mobile, and cloud — with the same tools chosen for reliability, scale, and long-term maintainability.
Next.js
Python
Flutter
Firebase
Supabase
Google Cloud
AWS
Microsoft Azure
Microsoft
Swift
Kotlin
Jetpack Compose
Vue.js
Node.js
Go
Rust
React Native
Next.js
Python
Flutter
Firebase
Supabase
Google Cloud
AWS
Microsoft Azure
Microsoft
Swift
Kotlin
Jetpack Compose
Vue.js
Node.js
Go
Rust
React Native
Native & cross-platform
Custom apps for advanced features
When products need deep native layers, platform-specific UX, or hybrid stacks beyond no-code — Kotlin, Swift, React Native with Expo, Flutter, and production stacks spanning Electron, Rust, Java, and Python.
Kotlin
kotlinlang.org/- Jetpack Compose for declarative Android UI with native performance
- Kotlin Multiplatform for shared logic across mobile targets
- Production Android layers integrated with Firebase and backend services
Swift
swift.org/- One codebase for the Apple ecosystem — iOS, iPadOS, macOS, watchOS, and visionOS
- SwiftUI and UIKit delivery with platform-native polish
- Emerging Swift for Android targets for shared logic where it fits the roadmap
React Native
reactnative.dev/- Expo as the standard framework base — routing, native APIs, and dev tools
- Native mobile plus web from a shared React codebase
- Desktop via Electron — Claude Code, VS Code, and cross-platform shells
- Bridge to native modules when APIs need platform-specific depth
- Cross-platform UI velocity with a single Dart codebase
- Custom plugins and platform channels for advanced integrations
- Pairs with FlutterFlow for rapid delivery and native extensions where needed
Need a scoped native build? Start a mobile project.
Robotics & Physics AI
The next production industry
Robotics and Physics AI are the next wave of production software — perception, simulation, control, and edge inference on real hardware. Ready to build and ship the next products from now.
- ROS — open robotics middleware for nodes, sensors, planning, and fleet-scale control
- NVIDIA — cloud simulation, Jetson edge AI, and hardware-accelerated perception stacks
- Physics AI — digital twins, sim-to-real, and vision-guided motion under safety envelopes
- Production path — from task spec and simulation to field tests and deployed edge systems
Delivery lines
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Physical AI & Robotics
AI that moves things — vision-guided control, simulation and edge inference for real machines.
(1) Task spec — motion and sensor needs inside a safety envelope. (2) Simulation — digital twin setup, policy training. (3) Perception + control — vision and planning stack as ROS 2 nodes. (4) Sim-to-real — calibration, field tests, failure modes. (5) Edge deploy — Jetson optimization with remote telemetry.
From $4,000
Fashion & retail
Fashion style eCommerce
Templates and inspiration for fashion-forward stores — from polished web designs to platform-ready layouts you can launch and sell through.
Web design & platform templates
Coming soonUpcoming templates for fashion eCommerce — full web designs and platform-ready builds prepared for sale so you can launch faster with a proven storefront structure.
Design collectives
Free to exploreA growing library of layout and UI collectives shared for free — mood boards, section patterns, and store flows to inspire your own fashion brand build.
Collaborations
Branding partners
Every partner rotates every five seconds — platform showcases and affiliate collections in one place.
Official partner · AI code editor
Cursor
Official Cursor partner for shipping production software with an AI-native editor — agentic workflows, multi-model routing, and deep codebase context in one workspace.
- Build with agents — delegate refactors, tests, and feature work while you stay in flow on the canvas.
- Whole-repo context — Cursor understands your stack, conventions, and files for precise edits at scale.
- Ship faster — tab completion, inline edits, and terminal-aware agents from prototype to production.