A tool demo
One-off- One prompt
- One manual export
- One person operating the tool
- No reusable data flow
- No monitoring or recovery
Saad Sohail · Full-Stack & Cloud Engineer
Independent HeyGen + LiveAvatar implementation engineerI turn HeyGen and LiveAvatar into working business systems.
I help teams connect AI video tools with CRMs, applications, automation platforms, and cloud infrastructure — from personalized video workflows and bulk localization to real-time avatar experiences.
APIs + webhooksn8n, Zapier + MakeHubSpot + custom CRMsCloud deployment + support
Pilot-first delivery Independent third-party specialist 24/7 support for active implementations
Available for focused implementation pilots
The implementation gap
Creating one AI video is easy. Running the workflow in production is the real work.
Once video generation depends on CRM data, templates, translations, approvals, webhooks, user sessions, delivery, and reporting, the job becomes a software and operations problem.
Production workflow
- Trigger
- Business data
- HeyGen / LiveAvatar
- Job status / webhooks
- Delivery
- CRM update
A production system
Repeatable- Live business data
- Automated triggers
- Reusable templates
- Async jobs and webhooks
- Validation and error handling
- Delivery, logging, and support
I build the software and automation around the AI tool so the workflow can run repeatedly, reliably, and inside the systems your team already uses.
Implementation services
What I can implement for your team
A focused set of services covering AI-video product flows, automation, integrations, localization, infrastructure, and ongoing technical support.
solution-personalized-video
Personalized video automation
Generate personalized sales, onboarding, or customer videos from CRM and form data without manually rebuilding every video.
Example flow
HubSpot deal stage → contact data → HeyGen template → generated video → email and CRM update
HubSpotTemplatesWebhooksPersonalized video
solution-localization
Bulk translation and localization
Turn a list or library of source videos into a trackable multilingual publishing workflow.
Example flow
Video list → target languages → translation jobs → status polling → output links → publishing notification
TranslationDubbingSubtitlesMultilingual publishing
solution-liveavatar
LiveAvatar assistants
Launch real-time avatar experiences for support, onboarding, guided demos, or interactive customer journeys.
Example flow
Website or app → LiveAvatar session → knowledge source → conversation → human handoff or session log
LiveAvatarReal-timeKnowledge baseSession logic
solution-automation
No-code and custom automation
Connect forms, spreadsheets, CRMs, email, Slack, and internal tools through no-code platforms or custom services.
Example flow
Business trigger → n8n / Zapier / Make → AI-video action → status update → downstream task
n8nZapierMakeCustom APIs
Reference architectures
See the system from trigger to outcome
These are the workflow designs I implement, shown end to end. Each one gets adapted to your stack during a pilot build.
01 / 03
CRM-triggered sales or onboarding video
Trigger to outcome
- 1CRM trigger
- 2Map data
- 3HeyGen
- 4Track job
- 5Deliver + update
Business situation
A new lead, customer, or deal reaches a specific stage and should receive a relevant personalized video.
- 1CRM stage or form submission triggers the workflow.
- 2Contact and deal fields are validated and mapped to a video template.
- 3HeyGen creates the video.
- 4The system tracks completion or failure through polling and/or webhooks.
- 5The result is sent, stored, and written back to the CRM.
I handle
- Template-variable mapping
- API request architecture
- Trigger and automation setup
- Status handling
- Delivery logic
- Logging and support
Operational outcome
A repeatable personalized-video workflow that operates from existing CRM activity.
02 / 03
Bulk video localization
Trigger to outcome
- 1Source list
- 2Batch jobs
- 3Track + retry
- 4Store outputs
- 5Notify team
Business situation
A content team needs to translate many videos into multiple languages without manually tracking every render.
- 1Source videos and language targets are added through a sheet, dashboard, or database.
- 2Translation jobs are created in controlled batches.
- 3The system tracks progress, failures, and retries.
- 4Completed outputs are stored with language and source metadata.
- 5The publishing team receives links or notifications.
I handle
- Input structure
- Batching
- Translation API requests
- Polling or webhook handling
- Retry logic
- Output storage
- Notifications
Operational outcome
A manageable localization pipeline instead of a collection of manual translation tasks.
03 / 03
LiveAvatar customer experience
Trigger to outcome
- 1User starts
- 2Create session
- 3Use knowledge
- 4Handle state
- 5Handoff + log
Business situation
A website or application needs an interactive avatar for onboarding, support, guided discovery, or product assistance.
- 1The user starts an avatar session from the product.
- 2The application creates and manages the LiveAvatar session.
- 3The avatar uses the approved knowledge or conversation logic.
- 4Session state, UI events, and failures are handled in the product.
- 5The experience ends with a handoff, action, or stored session result.
I handle
- Session lifecycle
- Frontend experience
- Backend integration
- Knowledge-flow design
- WebRTC and connection considerations
- Error states and operational support
Operational outcome
A customer-facing avatar experience that behaves like a product feature, not a disconnected demo.
Proof of work
HeyGen V3 Features Lab
A self-built Next.js playground that turns six HeyGen V3 capabilities into usable product flows. It demonstrates the product, API, automation, and async-job engineering behind real AI-video implementations.
The Lab runs against a live Enterprise API key, so it is not publicly hosted. Happy to walk through it on a call.
This is a self-built workflow lab and proof-of-concept, not a client project.
heygen-v3-features-lab
Video AgentAI Studio video generationVideo translationLipsync workflowTranslation proofreadingVoice cloning
Feature chapter
01 / 06
proof-video-agent
Video Agent
Create prompt-to-video jobs through a focused interface and follow the request from user input to generated result.
- Prompt and option management
- Request orchestration
- Loading and session states
- Job-history-friendly data structures
- Result rendering
- Retry and reset paths
Prompt-to-videoAPI orchestrationSession stateResult rendering
01 / 06 · proof-video-agent
Video Agent
Create prompt-to-video jobs through a focused interface and follow the request from user input to generated result.
- Prompt and option management
- Request orchestration
- Loading and session states
- Job-history-friendly data structures
- Result rendering
- Retry and reset paths
Prompt-to-videoAPI orchestrationSession stateResult rendering
02 / 06 · proof-video-generation
AI Studio video generation
Choose an avatar, voice, script, and generation options, then submit and track the video through completion.
- Structured input controls
- Typed payload construction
- Validation before submission
- Asynchronous job creation
- Status polling
- Output preview and result actions
Typed payloadsInput validationAsync statusOutput handling
03 / 06 · proof-video-translation
Video translation
Submit a source video, choose target-language settings, track the translation job, and surface the completed multilingual outputs.
- Source-video input handling
- Language and speaker configuration
- Translation request orchestration
- Progress and failure states
- Multilingual result handling
- Reusable output links
Localization flowJob lifecycleMulti-language outputsFailure states
04 / 06 · proof-lipsync
Lipsync workflow
Pair video and audio inputs, validate the required assets, launch the lipsync job, and display the completed media.
- Asset validation
- Payload composition
- Upload or URL input handling
- Asynchronous render tracking
- Error messaging
- Preview and download states
Asset validationPayload compositionRender trackingMedia output
05 / 06 · proof-proofreading
Translation proofreading
Review translated subtitle content, edit individual lines, resubmit corrections, and track the regenerated output.
- Subtitle or SRT data handling
- Editable line-level state
- Validation of corrected content
- Resubmission flow
- Version-aware result state
- Clear success and error feedback
SRT workflowEditable stateResubmissionVersioned output
06 / 06 · proof-voice-cloning
Voice cloning
Collect the required audio and consent inputs, create a reusable voice asset, and make it available to future generation workflows.
- Multipart or media input handling
- Consent-aware UI
- Voice creation lifecycle
- Returned voice-ID storage
- Reusable asset selection
- Success, error, and reset states
Media uploadConsent flowReusable voice IDAsset lifecycle
Async Job Handling
Track long-running generation, translation, lipsync, and voice jobs without freezing the product experience.
Webhook Management
Handle completion and failure events through resilient status logic and clear recovery paths.
Payload Architecture
Turn user and business inputs into clean, typed, validated requests for every capability.
This is the layer I bring to implementations: product UI, APIs, automation, infrastructure, and support working as one system.
One technical partner
From workflow idea to production support
You do not need one person for the interface, another for the API, another for automation, and another for deployment. I can connect those layers into one focused implementation.
Saad Sohail
Full-Stack & Cloud Engineer
The person you speak with builds it
Full-stack implementation
Product interfaces, backend services, data handling, and integration logic built around the actual user journey.
Automation and integrations
CRMs, forms, spreadsheets, internal tools, n8n, Zapier, Make, custom APIs, and webhooks connected into one flow.
Cloud and reliability
Environment setup, deployment, secrets, logs, monitoring, failure handling, and operational documentation.
Hands-on support
Testing, launch assistance, refinements, troubleshooting, and 24/7 support for active implementation clients.
Working stack
Next.js | React | TypeScript | Node.js | PostgreSQL | Docker | AWS | REST APIs | Webhooks | n8n | Zapier
I work as an independent engineer, so the person discussing the workflow is also the person responsible for the implementation.
Pilot-first delivery
Start with one workflow. Prove it. Then scale.
Instead of beginning with a large risky build, I help you select one clear business workflow and turn it into a working pilot with defined inputs, outputs, testing, and support.
01 / 04
Use-case review
What happens
I identify the user, trigger, business data, current tools, desired outcome, constraints, and success condition with you.
What you receive
A focused pilot brief and a clear definition of what should be built first.
02 / 04
Workflow blueprint
What happens
I map the product flow, HeyGen or LiveAvatar capability, API requests, data movement, automations, integrations, security considerations, and failure states.
What you receive
A system map, implementation plan, and pilot scope.
03 / 04
Pilot build
What happens
I build one usable end-to-end workflow, including the required interface, integration logic, testing, deployment support, and documentation.
What you receive
A working pilot that can be reviewed with real inputs.
04 / 04
Launch and support
What happens
I refine the workflow with you, monitor it, resolve issues, add the next highest-value features, and support the live implementation.
What you receive
A stable operating workflow and a practical roadmap for scaling it.
Start with a use case
Tell me the workflow you want to build.
Share the tools you use today, the manual process you want to remove, and the result you want the system to produce. I will help you identify a focused first pilot.
Focused pilot
Ready to scope- 01Use caseTrigger, tools, outcome
- 02System mapInputs, APIs, failure states
- 03Pilot buildOne end-to-end workflow
- 04OperateDeploy, monitor, support