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Claude, GPT, and Gemini API integration built into your product - by a dedicated engineering team.
Generative AI Services For US Product Teams A Remote Dedicated Developer
A remote developer who adds generative AI features to the product your US customers already pay for: drafting, summaries, document extraction and search over each customer's own data. Evals, cost tracking per feature and answers for enterprise security reviews come with every release.
Generative-AI Features From Empiric Infotech LLP
Empiric Infotech LLP provides generative AI services to US software companies that want AI inside their product, not in a separate demo. A remote dedicated developer builds the features your customers will use every day: a draft button in your editor, a summary of a long record, fields extracted from uploaded PDFs, search that answers from each customer's own data, a chart explained in plain English. US buyers check the work behind each feature. Enterprise customers ask whether their data trains a model, where it is processed and who can see it, so we use model endpoints whose terms exclude training on your data, keep each tenant's data separate in retrieval, and log every call. Healthcare products need PHI to stay inside a BAA, so model calls go through a provider that signs one with you, such as Azure OpenAI, Amazon Bedrock or Google Vertex AI. Your finance team will ask what the AI costs, so every feature reports its own token spend and latency. Your developer works in your GitHub and your AWS, Azure or Google Cloud account, joins your morning standup on Eastern time, and ships behind feature flags, with a senior team lead reviewing and testing each release. Our closest US reference is EndoDNA, where clinicians ask an AI assistant about labs, DNA and history and get answers streamed in real time, built by a single dedicated developer.
What our generative AI services deliver for US product teams
AI features shipped inside your product, with the answers enterprise buyers, security reviewers and your finance team will ask for.
Features customers use daily
Drafting and rewriting in your editor, summaries of long records or threads, extraction from invoices, contracts or medical forms into structured fields, classification of inbound items, and natural-language search over each customer's data. Each one ships behind a flag and rolls out by cohort.
Answers for enterprise security reviews
Model endpoints whose terms exclude training on your data, tenant isolation in retrieval so one customer's documents never reach another's answer, PII redaction before prompts where it is needed, and a log of every call. Your security team gets a short written data flow for each feature.
HIPAA-ready AI for health products
For PHI, model calls go through a provider that signs a BAA with you, only the minimum necessary data is sent, and outputs are stored under the same access controls as the rest of the record. EndoDNA, our US healthcare reference, runs its AI assistant inside a HIPAA-compliant platform.
Structured outputs your code can trust
Responses validated against a JSON schema or returned through tool calls, so the product never parses free text with a regex. Streaming where users wait on text, with cancel and retry built in.
Evals and cost per feature
A test set from real, anonymised inputs scored on every prompt or model change, plus a dashboard of token cost, latency and error rate for each feature. Prompt caching and smaller models on easy inputs keep the margin where finance expects it.
Room to change models
Prompts and evals are written so you can move between Claude, GPT, Gemini or an open model on Bedrock when price or quality shifts, and see on your own data whether the switch helped.
How a US generative AI engagement starts
A first AI feature working inside your app in the first week, built around your morning on US time.
A call in your morning
Thirty minutes in your Eastern, Central or Pacific morning. You show us the product, the feature you want, the data it would use and how you would judge it: adoption, time saved, tickets avoided or deals unblocked.
A written feature plan within 24 hours
The model and SDK we would use and why, the prompt and output schema, the eval set, the data flow your security team will ask about, a cost estimate per call and an estimate on both plans. The NDA, IP assignment and our W-8BEN-E go over together.
A first feature behind a flag
Your developer starts within 48 hours and has the feature working end to end inside your app on real inputs, behind a feature flag with evals running, by the end of the first week. Day 7 of the monthly plan is a real decision point, with a full refund if it is not a fit.
Monthly or hourly after that
A full-time developer billed monthly in USD, or hours tracked to the minute for one defined feature. Add a developer as the AI roadmap grows, or stop with seven days' notice.
Generative AI development pricing for US teams: hourly or monthly
Both plans are invoiced in USD and paid by ACH, wire or card. Monthly gives you a full-time generative AI developer for 160 to 172 hours, billed upfront, for a roadmap of AI features. Hourly suits one defined piece of work, such as a single feature, an eval suite or a model migration. The AI hourly rate is higher than our standard hourly rate because the work comes in short expert bursts; the monthly rate is the same as any Empiric Infotech engagement. Model tokens, embeddings and vector database costs are billed to your own accounts at cost.
Hourly plan
- A generative AI developer, exclusive to you while hours are booked
- Time tracked to the minute, with a weekly report and demo
- Suited to a single feature, or tuning one you already shipped
- Your GitHub, your cloud and your model keys from day one
- A senior team lead reviews and tests every release
Monthly plan
- A full-time generative AI developer, 160 to 172 hours a month
- Standups on your Eastern-time morning, a written handover daily
- One USD invoice a month, with a W-8BEN-E on file
- 7-day risk-free trial, then seven days' notice to stop
- Eval scores and per-feature cost with every release
Dedicated team
- Two or more developers plus a senior team lead
- For AI features across several products or surfaces
- Add a developer, or a designer for AI interfaces, within 48 hours
- Data-flow write-ups for enterprise security reviews
The first 90 days of generative AI features with a US team
A typical first quarter, from a feature behind a flag to a measured part of the product.
- Week 1
A first feature behind a flag
Access to the repo and cloud, the model and SDK chosen, the feature working inside your app on real inputs, an eval baseline and cost logging per call. The monthly trial decision falls on day 7.
- Month 1
Rolled out to real customers
The feature released to a first cohort, then wider, with feedback captured in the product, evals growing from real cases, and a dashboard of cost, latency and usage per feature.
- Month 2
The second feature and the security write-up
A second feature built on the same eval and logging setup, fallbacks for provider outages, and a data-flow write-up ready for your enterprise customers' security questionnaires.
- Month 3
Cost and quality tuning
Prompt caching, cheaper models on easy inputs and a model comparison on your evals, so quality holds while the cost per feature drops. Next quarter's AI roadmap is planned with product.
A dedicated generative AI developer vs a US AI consultancy, an AI feature platform, or an in-house AI engineer
| Empiric Infotech (dedicated generative AI developer) | US AI consultancy (project) | AI feature platform | In-house AI engineer | |
|---|---|---|---|---|
| Where the feature lives | In your codebase, behind your feature flags | Delivered as a project, sometimes as a separate service | Behind the vendor's API and prompt store | In your codebase |
| Enterprise security answers | A data flow per feature, no training on your data, tenant isolation | Per the statement of work | The vendor's SOC 2 report and terms | Whatever your team documents |
| Health data | Model calls under a BAA; minimum necessary data | Per firm | Depends on the vendor's BAA | Your compliance program |
| Evals and cost per feature | On every change, with a cost dashboard per feature | Often at delivery only | Platform dashboards | If your team builds them |
| Base cost | A flat monthly fee, or an hourly rate for one feature | A project fee plus change orders | A subscription plus your team's integration time | $135,980 median pay for a US software developer (BLS, May 2025), before benefits |
| Time to start | 48 hours | Weeks: proposal, statement of work, kickoff | Days to sign up, weeks to integrate | 3 to 5 months to hire |
| Code and prompts | Yours from day one, in your repo | Yours on final payment | Prompts stored in the vendor's system | Yours |
The comparison describes how each option usually works, not any one provider.
Working hours and US time zone overlap
Our team works 09:30 AM - 07:30 PM IST and a project manager is on call 07:30 AM - 11:00 PM IST, Monday to Friday. Here is exactly when that lands for clients in the US, Europe and Australia, your region first.
US Eastern (New York, Boston, Atlanta) - full team online 12:00 AM - 10:00 AM, project manager 10:00 PM - 1:30 PM (next day).Live cover across the edges of your day, your morning and your evening, with a project manager who replies the same business day.
US Pacific (Los Angeles, San Francisco, Seattle) - full team online 9:00 PM - 7:00 AM (next day), project manager 7:00 PM - 10:30 AM (next day).We are online through your evening and overnight, and your project manager sets live calls in your morning so you are never blocked.
UK & Ireland (London, Dublin) - full team online 5:00 AM - 3:00 PM, project manager 3:00 AM - 6:30 PM.
Central Europe (Berlin, Paris, Amsterdam, Madrid) - full team online 6:00 AM - 4:00 PM, project manager 4:00 AM - 7:30 PM.
Australia East (Sydney, Melbourne, Brisbane) - full team online 3:00 PM - 1:00 AM (next day), project manager 1:00 PM - 4:30 AM (next day).
Want it to the half-hour in your own time? Slide through your day and book a slot below.
Why US product teams ship generative AI with a dedicated developer
A generative AI feature is easy to demo and hard to keep good. Real inputs are messier than the demo set, models change underneath you, costs grow with usage, and enterprise customers start sending security questionnaires about it. A project that ends at launch leaves all of that with your core team.
A dedicated developer owns it: grows the eval set from real failures, tracks cost and latency per feature, writes the data-flow answers for security reviews and moves to a better or cheaper model when the scores support it. Hiring that person in the US is slow and expensive; a software developer's median pay is $135,980 a year (BLS, May 2025) before benefits, and engineers with production AI experience are in short supply.
The overlap suits product work. Your morning standup on Eastern time sets the priorities, the developer builds and runs evals while you are offline, and a written handover is waiting when you start. You own the code, prompts and model accounts from day one, the invoice is one USD bill a month, and you can stop with seven days' notice.
Recent AI, product, and integration work
EndoDNA: an AI assistant inside a clinical platform
A conversational assistant that answers clinicians' questions about labs, DNA and history in plain language, streamed over Server-Sent Events, with AI-assisted care plan templates and every conversation saved. Part of a HIPAA-compliant, multi-tenant SaaS.
Read case studyTherapyCue: SOAP notes generated from live sessions
Real-time transcription with failover between providers, AI suggestions during the session and structured SOAP notes generated afterwards, designed to stay clinically grounded. Built with a BAA acceptance workflow and audit tracking.
Read case studySuperintelligence: a generative AI assistant
A personal assistant that generates text for study, content, email, health and business questions, with saved and editable history, an incognito mode and subscription plans. Built on OpenAI.
Read case studyTell us the AI feature your customers keep asking for
Share the product, the feature and the data it would use. Within 24 hours you get a feature plan with the model, the eval set, the data flow for your security team and an estimate on both plans. Your developer can start within 48 hours on Eastern-time overlap.
Who This Is For
Built for Businesses Ready to
Harness AI Creativity at Scale
We partner with founders, product teams, and innovators who want AI that doesn’t just automate - it creates. From generating personalized content to building adaptive AI tools, we make sure it works for your real-world needs.
This Is for You If:
You need AI-generated outputs that meet brand, compliance, or industry standards
You’ve tried ChatGPT or Midjourney but can’t scale quality or integrate results
You want AI that can create across multiple formats : text, image, video, or code
You’re looking for secure, private AI that learns from your data without leaking it
You want generative models fine-tuned for your audience, domain, or products
You’re done with one-size-fits-all tools and need a system tailored to your workflows
What We Do
We Build Generative AI
Systems That Create Like Experts, Operate Like Engineers
We don’t stop at “prompt engineering.” We architect full-stack generative AI solutions - from model selection and fine-tuning to API integration and deployment - all designed for accuracy, reliability, and scalability.
What We Build:
AI-powered content creation pipelines (text, image, audio, video)
Domain-specific fine-tuned LLMs for better accuracy & compliance
Intelligent content moderation, filtering, and fact-checking layers
Multi-format generation workflows integrated into your existing tools
Fully automated creative processes - from ideation to publishing
Platforms & Tools We Work With (and Beyond):
We’re platform-agnostic - if it can generate, we can integrate and optimize it.
Core Capabilities
Text-to-Anything Content Generation
Produce high-quality articles, ad copy, product descriptions, and more - tailored to your brand voice and optimized for SEO or engagement.
Powered by: Chat-GPT, Claude, Gemini, custom fine-tuned LLMs
Image & Creative Asset Generation
From photorealistic product images to AI-assisted illustrations and marketing creatives - generated in seconds, not days.
Built with: Midjourney, DALL·E, Stable Diffusion
Custom Fine-Tuned Models
Train models on your proprietary data to create industry-specific AI systems that understand your niche, tone, and workflow.
Tech behind the scenes: OpenAI fine-tuning, LoRA, embeddings, Pinecone
Multimodal AI Experiences
Combine text, image, and audio generation into unified tools - for example, AI that can write a script, create visuals, and generate voiceovers in one flow.
Built using: OpenAI, ChatGPT, Runway, ElevenLabs
Data-to-Insight AI Reports
Turn raw datasets into insightful summaries, visuals, and recommendations - without a single pivot table.
Integrated into: Notion, Data Studio, PowerBI, and custom dashboards
How We Build Systems That Scale
A Collaborative Process, Built for Your Creative and Data Needs
We don’t just plug in AI APIs - we design, train, and optimize generative AI systems around your goals, workflows, and audience.
Discovery & Use Case Mapping
We explore your goals, datasets, and workflows - identifying where generative AI can replace manual work or unlock new capabilities.
Outcome: Clear ROI-backed AI roadmap
Data Preparation & Model Selection
We prepare your content/data, choose the right base models, and plan whether fine-tuning or prompt engineering is needed.
Outcome: Optimized, domain-specific AI foundation
Prototype & Validate
We create a functional prototype to showcase capabilities and gather feedback early.
Outcome: Stakeholder alignment and proof of value
Full Development & Integration
We build and integrate the generative AI solution into your tools, systems, and workflows.
Outcome: AI running seamlessly in production
Onboarding & Creative Enablement
We train your team to use, adapt, and improve the AI’s outputs - ensuring long-term productivity.
Outcome: Confident, in-house AI adoption
Optimization & Continuous Learning
We monitor performance, retrain when needed, and adapt to your evolving business goals.
Outcome: AI that stays relevant and grows with you
Industries We Build For
Generative AI Solutions for Every Industry
From innovative startups to enterprise-scale operations, we deploy generative AI that adapts to your sector’s unique workflows and challenges.
Industries We Serve:
SaaS & Startups
Content generation, customer onboarding, product documentation
E-commerce
Automated product descriptions, personalized recommendations, support chat
HR & Recruitment
AI-powered screening, resume parsing, interview question generation
Healthcare Admin
Clinical documentation assistance, patient communication, compliance reports
Logistics & Supply Chain
Route optimization, predictive demand planning, document automation
EdTech
Adaptive learning content, grading automation, personalized study materials
If your industry requires nuanced, context-aware AI, we can build it.
Why Empiric Infotech for Generative AI
Why Teams Trust Empiric Infotech for Generative AI Development
We don’t just integrate AI APIs - we design, fine-tune, and deploy custom generative AI systems built for real business impact.
Our Approach:
Domain-specific fine-tuning
AI that understands your industry’s language and rules
Custom model workflows
No one-size-fits-all templates
Privacy & security first
Data-safe solutions, self-hosted options available
Rapid prototyping
Validate with a functional v1 before scaling
Founder-led delivery
Direct collaboration with decision-makers
Post-launch iteration
Continuous improvement for lasting value
Tools We Work With
Flexible Tech Stack. Built Around Your Needs.
We leverage the best in AI, LLMs, and supporting infrastructure - and adapt the stack to fit your business goals.
Stack Includes:
AI & Language Models
Automation Platforms
AI Frameworks
Voice & Communication
Backend & Database
OpenAI
Claude
Gemini
Mistral
Meta LLaMA
Prefer open-source, enterprise-grade, or hybrid? We’ll build with what makes sense for you.
Why Businesses Choose Empiric Infotech LLP?
Working with Empiric Infotech has been exceptional from start to finish. Their team is incredibly talented, highly responsive, and consistently delivers at a world-class level across UI/UX and back-end development. No matter the challenge or complexity we have brought to them, they have always found a solution. Having a development partner you can fully trust is invaluable, and I would highly recommend them to any company or founder looking for an elite development team.
Founder and CEO Roamate
We worked with Empiric Infotech to build a chatbot for our children’s theater project, and we’re so glad we did. The team was fast, responsive, and kept working until everything was perfect. The project was delivered on time, within budget, and the end result looks and works great. We’re truly grateful for their support
E-commerce Brand
I found in Empiric Infotech an excellent partner to build my blockchain platform. They are professional, knowledgeable, and supportive at every stage. Even after launch, we keep collaborating - and the results have always been wonderful
Founder Winupdraws
I was looking for a skilled software team to help me transform my prototype into a complete app. Empiric Infotech not only delivered exactly what I needed, but also added custom features, backend notifications, and guided me through publishing on both app stores. Their communication was smooth and reliable. I can gladly recommend them.
Founder and consultant at tak innovation
We needed support to strengthen our technical platform, and Empiric Infotech delivered exactly what we were looking for. The team was professional, responsive, and kept everything on track with both time and cost. As our company grows, we’re glad to have them as a trusted partner and would happily recommend their services.
Founder Skapasaga
Finding the right agency for our My Ayur app was challenging, but Empiric Infotech delivered exactly what we needed. Over past months, their expertise in FlutterFlow and MongoDB stood out, consistently delivering high-quality work. Professional, friendly, and reliable - a partner I would confidently recommend.
Founder and CEO Sresht Ayur
Working with Empiric Infotech has been exceptional from start to finish. Their team is incredibly talented, highly responsive, and consistently delivers at a world-class level across UI/UX and back-end development. No matter the challenge or complexity we have brought to them, they have always found a solution. Having a development partner you can fully trust is invaluable, and I would highly recommend them to any company or founder looking for an elite development team.
Charli SharpFounder and CEO Roamate
We worked with Empiric Infotech to build a chatbot for our children’s theater project, and we’re so glad we did. The team was fast, responsive, and kept working until everything was perfect. The project was delivered on time, within budget, and the end result looks and works great. We’re truly grateful for their support
Eva MesmanE-commerce Brand
I found in Empiric Infotech an excellent partner to build my blockchain platform. They are professional, knowledgeable, and supportive at every stage. Even after launch, we keep collaborating - and the results have always been wonderful
John FelipeFounder Winupdraws
I was looking for a skilled software team to help me transform my prototype into a complete app. Empiric Infotech not only delivered exactly what I needed, but also added custom features, backend notifications, and guided me through publishing on both app stores. Their communication was smooth and reliable. I can gladly recommend them.
Andrzej KarelFounder and consultant at tak innovation
We needed support to strengthen our technical platform, and Empiric Infotech delivered exactly what we were looking for. The team was professional, responsive, and kept everything on track with both time and cost. As our company grows, we’re glad to have them as a trusted partner and would happily recommend their services.
Fredrik HagenFounder Skapasaga
Finding the right agency for our My Ayur app was challenging, but Empiric Infotech delivered exactly what we needed. Over past months, their expertise in FlutterFlow and MongoDB stood out, consistently delivering high-quality work. Professional, friendly, and reliable - a partner I would confidently recommend.
Eshu MiddhaFounder and CEO Sresht Ayur
Compliance & Security
Generative AI Without Compromising Privacy or Control
What We Deliver:
GDPR-compliant data handling
Role-based access controls (RBAC)
Self-hosting options
Audit logging & retention governance
Built for teams who want the power of generative AI - without the risk.
Let’s Build the Generative AI Solution
Your Business Deserves
FAQs
Answers to Common Questions - From Founders, Ops Teams & Tech Leads
Frequently asked questions
They are the design, build and upkeep of AI features inside a product you already run: drafting, summarising, extracting data from documents, classifying, and answering questions from a customer's own data. Empiric Infotech provides them through a remote dedicated developer who works in your codebase and cloud, ships each feature behind a flag and tests it against evals before release.
A flat monthly fee for a full-time developer (160 to 172 hours), or an hourly rate for one defined feature, both in USD. Current rates are in the pricing section above, and model usage is billed to your own accounts at cost. For comparison, a US software developer's median pay is $135,980 a year (BLS, May 2025) before benefits.
Two hours of live overlap with US Eastern time, 8:00 to 10:00 AM ET (one hour from November to March), and the project manager is available until 1:30 PM ET. Central teams overlap from 8:00 to 9:00 AM CT, while Mountain and West Coast teams meet the project manager for the standup and work from a written handover each morning.
One invoice a month in USD, paid by ACH, wire or card, and we provide a completed W-8BEN-E for your accounts team. Empiric Infotech also has a US office in Bridgeville, Pennsylvania.
No. We use model endpoints whose terms exclude training on your inputs and outputs, such as the OpenAI and Anthropic APIs, Azure OpenAI, Amazon Bedrock or Google Vertex AI, with the keys in your own accounts. Each customer's data stays isolated in retrieval, and every call is logged.
Yes. Model calls go through a provider that signs a BAA with you, only the minimum necessary data is sent, and outputs are stored under the same access controls as the rest of the record. EndoDNA, a HIPAA-compliant platform with an AI assistant, was built by a single dedicated developer from Empiric Infotech.
Whichever wins on your evals at an acceptable cost: Claude, GPT and Gemini, or open models such as Llama on Bedrock. On the code side, the official Anthropic and OpenAI SDKs for most features, the Vercel AI SDK for streaming interfaces in Next.js, and LlamaIndex or LangChain when retrieval is the centre of the feature.
A first version usually works inside your app, behind a flag, by the end of the first week, and reaches a first group of real customers within the first month. Complex features are split so part of the value ships early.
You do, fully. The NDA and IP assignment are signed before work starts, and the code, prompts and eval sets live in your repository from the first commit. You can stop with seven days' notice, and the first 7 days on the monthly plan are a risk-free trial.
Yes. EndoDNA's clinical AI assistant was built for a US client by a single dedicated developer, and Superintelligence, a US generative AI assistant, by a two-developer team. Typical US engagements run 6 to 18 months.
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