Fenloz Services
Custom software development & AI engineering services
Hire Fenloz to design and ship production software — RAG and LLM systems, Python/Go backends, SaaS product features, data pipelines, and integrations — as scoped engineering engagements for startups and product teams worldwide.
Software development services we offer
Six packaged engineering offers with clear deliverables. Each engagement is scoped after discovery so projects ship with fixed boundaries — not open-ended staff augmentation by default.
AI & RAG Systems
Included
- Use-case scoping and data readiness review
- Ingestion, embeddings, and retrieval pipeline
- Grounded responses with evaluation basics
- API / UI handoff and deployment guidance
Not included: Open-ended research without a ship target; Ongoing model ops without a partner retainer.
Best for: Teams that need AI that answers from their own docs and systems
Typical timeline: 3–6 weeks
Backend & Distributed Systems
Included
- Service design and tech stack recommendation
- API / worker / queue implementation
- Failure handling, logging, and basic observability
- Deployed service + operational notes
Not included: 24/7 on-call without a retainer; Full platform rewrites from scratch.
Best for: Startups and product teams needing reliable backend infrastructure
Typical timeline: 2–6 weeks
Product & SaaS Engineering
Included
- Requirements → implementation roadmap
- Full-stack delivery for agreed scope
- PR-quality code, reviews, and documentation
- Launch support and knowledge transfer
Not included: Unlimited feature backlog under one fixed fee; In-house team replacement without a retainer.
Best for: Founders and teams who need senior builders, not just extra hands
Typical timeline: 4–12 weeks
Data Pipelines & Analytics
Included
- Source audit and pipeline design
- Ingestion / transform jobs (e.g. Celery, Airflow)
- Warehouse or DB landing models
- Dashboard wiring (Power BI / Tableau / custom)
Not included: One-off spreadsheet cleanup as a project; Managed BI licensing costs.
Best for: Teams drowning in manual exports and unreliable reporting
Typical timeline: 2–5 weeks
Integrations & Workflow Automation
Included
- Integration map and failure modes
- Webhook / API connectors
- Automation flows with retries and dead-letter handling
- Monitoring hooks and runbook notes
Not included: Ad buying or creative production; Tool subscription fees.
Best for: Ops-heavy businesses stitching multiple vendors into one workflow
Typical timeline: 1–4 weeks
Fractional Tech Lead
Included
- Weekly working sessions
- Architecture and tech-stack guidance
- PR / design reviews
- Hiring and delivery process advice
Not included: Hands-on feature factory hours beyond agreed capacity; People management of your payroll staff.
Best for: Early teams that need senior technical direction
Typical timeline: Month-to-month
Commercial terms are scoped after discovery. Cloud, LLM API, and third-party tool costs are billed separately unless a quote says otherwise.
Technologies we build with
Production stacks for AI systems, backends, data pipelines, and product engineering — chosen to fit your environment, not a one-size template.
- Python
- Go
- TypeScript
- JavaScript
- SQL
- FastAPI
- Django
- Flask
- Gin
- Node.js
- React
- React Native
- REST APIs
- WebSockets
- PostgreSQL
- MySQL
- MongoDB
- SQLite
- Snowflake
- Redis
- RabbitMQ
- Celery
- AWS SQS
- EventBridge
- Airflow
- dbt
- NumPy
- Pandas
- LangChain
- OpenAI API
- RAG / Embeddings
- ChromaDB
- Vector DBs
- NLP
- Prompt Engineering
- PyTorch
- TensorFlow
- AWS
- GCP
- EC2
- RDS
- S3
- ECS
- Docker
- Kubernetes
- CI/CD
- Azure DevOps
- Power BI
- Tableau
- Webhooks
- Payment Integrations
- Python
- Go
- TypeScript
- JavaScript
- SQL
- FastAPI
- Django
- Flask
- Gin
- Node.js
- React
- React Native
- REST APIs
- WebSockets
- PostgreSQL
- MySQL
- MongoDB
- SQLite
- Snowflake
- Redis
- RabbitMQ
- Celery
- AWS SQS
- EventBridge
- Airflow
- dbt
- NumPy
- Pandas
- LangChain
- OpenAI API
- RAG / Embeddings
- ChromaDB
- Vector DBs
- NLP
- Prompt Engineering
- PyTorch
- TensorFlow
- AWS
- GCP
- EC2
- RDS
- S3
- ECS
- Docker
- Kubernetes
- CI/CD
- Azure DevOps
- Power BI
- Tableau
- Webhooks
- Payment Integrations
How custom software engagements work
A repeatable delivery process so you get working software, clear ownership, and a clean handover — not endless discovery slides.
Step 1
Discovery
We understand the problem, constraints, and what “done” looks like for your team.
Step 2
Proposal
Fixed scope, timeline, commercial terms, and exclusions — so you know exactly what you're buying.
Step 3
Build
We design, implement, and ship in your repos and cloud — with regular demos.
Step 4
Handover
Docs, training, and optional partner retainer so your team can own what we shipped.
Why teams hire Fenloz for custom development
We have led delivery of SaaS platforms serving 50+ businesses, event-driven systems at hundreds of thousands of messages per month, production RAG, and full-stack product work across backend, frontend, and mobile. You get builders who have shipped — not a staffing marketplace.
Looking for the product instead? Explore Fenloz features or platform pricing. Prefer to talk first? Contact the team.
Frequently asked questions about Fenloz Services
Straight answers for teams evaluating a software development partner for AI, backend, data, or product work.
What software development services does Fenloz offer?
- Fenloz Services delivers custom software work for other companies: AI and RAG systems, backend and distributed systems, SaaS/product engineering, data pipelines and analytics, API integrations and workflow automation, and fractional tech leadership. This is separate from the Fenloz SaaS product subscription.
Is Fenloz Services the same as the Fenloz SaaS platform?
- No. Fenloz is a self-serve SaaS product for CRM, social commerce, and automation. Fenloz Services is a separate custom software development practice — we design and build systems for clients who need engineering delivery, not product configuration.
Do you build production RAG and LLM applications?
- Yes. We design and ship retrieval-augmented generation pipelines, knowledge bots, agents, and natural-language interfaces over private documents and databases — including ingestion, vector search, grounded answers, and basic evaluation.
Which technologies do you use for custom software projects?
- Typical stacks include Python, Go, TypeScript, FastAPI, Django, Gin, React, PostgreSQL, MongoDB, Redis, RabbitMQ, Celery, Airflow, dbt, LangChain, ChromaDB and other vector databases, OpenAI APIs, AWS, GCP, Docker, Kubernetes, and BI tools like Power BI and Tableau. Final stack choices follow your constraints and the engagement scope.
How do custom software engagements with Fenloz work?
- We start with scoped discovery, propose fixed deliverables and exclusions, build in your repos and cloud with regular demos, then hand over with documentation — or continue on a retainer for iteration and technical leadership.
Who are Fenloz software development services for?
- Founders, startups, and product teams that need senior engineering for AI systems, backends, data pipelines, integrations, or fractional tech leadership — especially when hiring a full in-house team is slower or more expensive than a scoped engagement.
Do you work remotely with teams outside India?
- Yes. We work remotely with clients worldwide. Discovery calls, delivery, and handover are designed for distributed collaboration across time zones.
Ready to scope a software project?
Tell us what you need to ship. We will recommend a scoped engagement — or tell you if buying software beats a custom build.