Generative AI Development Company
Custom generative AI development services for teams that need more than a chatbot: LLM applications, AI agents, RAG systems and AI copilots, built on your data and ready for production.
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Transforming Businesses with Proven Results
Faster development, greater efficiency, trusted globally, and driven by referrals.
savings with AI-powered Engineering
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efficiency boost for businesses
of new clients come from referral
What Do Our Generative AI Development Services Include?
Calling a model API takes an afternoon, but whether a generative AI feature survives contact with users depends on everything around the call: retrieval quality, evaluation, guardrails, cost control and what happens when a provider retires the model you built on. As a generative AI development services company, we spend most of each project on that surrounding work. If you need engineers inside your own team instead of a delivered project, you can hire AI developers from the same group.
Generative AI Consulting
We assess your data readiness, pick the use cases with clear payback, and settle build versus buy, model selection and infrastructure before any development starts.
Custom Generative AI Development
Generative AI applications built for your workflow: document Q&A, report generation, summarization, extraction pipelines and in-app copilots. We handle requirements, architecture, prompts, model integration, testing, deployment and monitoring.
LLM Integration Services
Large language models connected to your CRM, ERP, healthcare platform or customer-facing app through custom APIs and middleware. Well-built RAG pipelines ground the answers in your own documents and data, usually long before fine-tuning is needed.
LLM Fine-Tuning & Model Training
LoRA and QLoRA fine-tuning of open-weight models such as Llama, Mistral and Qwen, or of commercial models, on your proprietary data when prompting and retrieval aren't enough. Every tuned model is scored against an evaluation set before it ships.
Enterprise Generative AI Solutions
SSO, role-based access, audit logging, data residency and multi-tenant architecture, plus content-safety guardrails, PII detection and cost controls.
Generative AI Maintenance & Optimization
Performance monitoring, prompt optimization, API cost management, retraining and model upgrades. Providers retire models and APIs on a schedule: OpenAI shut down its Assistants API on August 26, 2026, and Anthropic retires Claude Sonnet 4.5 on November 30, 2026. We plan those migrations before they become outages.
AI Models & Platforms We Work With
From leading commercial models like GPT to powerful open-source and specialized AI systems, our team of experts excels at harnessing these technologies to drive real business impact.
Specialized Models
Technology Stack
What We Build: Generative AI Solutions
LLM-Powered Applications
Custom applications built on large language models — document Q&A systems, AI writing assistants, automated report generators, and intelligent search. We work with both commercial APIs (OpenAI, Anthropic) and open-source models (Llama, Mistral, DeepSeek) based on your cost, accuracy, and data privacy requirements.
Common builds:
- Internal knowledge base Q&A connected to company documents
- Document summarization and data extraction pipelines
- AI-powered search across enterprise databases
- Automated report generation from structured data
- Multi-language translation and localization systems
AI Agents & Autonomous Workflows
AI agents that plan, reason and carry out multi-step tasks, with an approval step on any action that changes data. Our custom AI agent development work uses the OpenAI Agents SDK, LangGraph, CrewAI and MCP servers, from customer support agents that resolve tickets end to end to research agents that pull data from several sources.
Common builds:
- Customer support agents with memory and tool use
- Sales prospecting agents that research leads and draft outreach
- Data pipeline agents that extract, clean, and load information
- Internal workflow agents for approvals, scheduling, and reporting
- Multi-agent systems where specialized agents collaborate on complex tasks
RAG Systems & Enterprise Search
Retrieval-Augmented Generation systems that connect LLMs to your private data — documents, databases, APIs — without expensive fine-tuning. Production-grade RAG pipelines with hybrid search (semantic + keyword), re-ranking, chunk optimization, and citation tracking.
Common builds:
- Legal document search across 100K+ contracts
- Medical knowledge bases for clinical decision support
- Product catalog AI search for e-commerce
- Internal policy and compliance document assistants
- Technical documentation search for engineering teams
AI Copilots & Assistants
Custom AI copilots embedded directly into your product or internal tools. Unlike generic chatbots, our copilots understand your domain, access your data in real-time, and take actions within your application — editing records, triggering workflows, and surfacing insights proactively.
Common builds:
- In-app AI assistants for SaaS products
- Sales copilots that surface deal insights and draft proposals
- Developer copilots for code review and documentation
- HR copilots for onboarding, policy Q&A, and leave management
- Customer success copilots with account health scoring
Conversational AI & Chatbots
Intelligent chatbots that go beyond scripted responses — multi-turn conversations with context retention, sentiment awareness, and seamless human handoff. Deployed on web, mobile, WhatsApp, Slack, and Microsoft Teams.
Common builds:
- Customer service bots with order tracking and returns handling
- Appointment scheduling assistants for healthcare and services
- Lead qualification chatbots for sales teams
Internal IT help desk bots with ticket creation - Multi-lingual chatbots for global customer bases
Content Generation Platforms
AI-powered content creation systems for marketing teams, publishers, and e-commerce — from product descriptions at scale to personalized email campaigns. Built with brand voice controls, fact-checking guardrails, and human approval workflows.
Common builds:
Product description generators for e-commerce catalogs (1,000s of SKUs)
Blog and article drafting assistants with SEO optimization
Personalized email campaign generators
Social media content creation and scheduling tools
Marketing copy variations for A/B testing
Generative AI Solutions by Industry
From startups to enterprises, from Generative AI in fintech to healthcare providers, our generative AI development services cater to a wide range of businesses.
Healthcare & Life Sciences
Clinical documentation drafts, patient-message triage, intake assistants and prior-authorization summaries, built on BAA-covered model endpoints with PHI redacted before prompting and a clinician reviewing anything that reaches a chart. Our HIPAA-compliant AI app for autism caregivers follows that pattern.
Fintech & Financial Services
Generative AI for fraud narrative generation, regulatory report drafting, customer onboarding chatbots, and investment research summarization. Built with SOC 2 and PCI-DSS compliance.
E-commerce & Retail
AI-powered product descriptions at scale, visual search, personalized recommendation engines, and customer service chatbots. Generative AI that directly drives revenue.
SaaS & Enterprise Software
Generative AI features that make your SaaS product smarter — in-app AI copilots, intelligent search, automated onboarding, and AI-powered analytics. Built as embeddable modules or standalone microservices.
Education & E-Learning
AI tutoring systems, automated content generation, assessment creation, and personalized learning paths. Generative AI that adapts to each student's pace and learning style.
Legal & Professional Services
Document analysis, contract review, legal research summarization, and compliance monitoring. Generative AI that handles the repetitive work so professionals can focus on high-value tasks.
How We Work: From Discovery to Deployment
Discovery & Use Case Definition (Week 1)
We assess your business goals, data, and infrastructure to identify high-impact AI use cases and recommend the right model strategy: commercial API, open-source, or hybrid.
Proof of Concept (Week 2–4)
We build a working PoC to validate feasibility, accuracy, and user experience — testing model performance on your actual data before committing to full development.
Production Development (Week 4–12)
Full development of your generative AI application: backend APIs, frontend integration, data pipelines, security controls, and testing with production-grade guardrails.
Launch & Continuous Optimization
Deployment, monitoring, and ongoing optimization. We track model performance, manage API costs, and implement new model versions to keep your AI system accurate and cost-effective.
Why Choose Tech Exactly as Your Generative AI Development Company?
From model selection to deployment, here's why companies choose us for generative AI.
We build the whole stack.
A generative AI development agency that only wraps an API call in a UI leaves you with a demo. We build the data pipelines, RAG architecture, prompt engineering, content safety, caching and monitoring that make a gen AI feature production-ready.
No lock-in to one model vendor.
We work across OpenAI, Anthropic, Google, Meta, Mistral and open-weight models, and the model sits behind an interface in your code. When a better or cheaper model ships, switching is a configuration change plus an evaluation run, not a rewrite.
Security from day one.
Data residency controls, PII detection and masking, audit logging, and HIPAA, SOC 2 and GDPR documentation. Our guardrails are designed around the risks in the OWASP Top 10 for LLM Applications, and risk documentation follows the NIST AI Risk Management Framework. It's the same checklist we use to audit your AI system before production, applied from the first sprint.
Costs kept in check.
Caching, prompt optimization, model routing (cheaper models for simple tasks, stronger ones for complex tasks) and usage monitoring go in from the start. Our clients typically see 40–60% lower API costs compared to unoptimized implementations.
AI experience, not a pivot.
Tech Exactly has built AI systems for over a decade: recommendation engines, NLP pipelines, computer vision and predictive models. Our team built the GenAI-powered nature identification app that recognized 2M+ species and attracted 1M+ users within months.
Read The Testimonials
Hear our trusted customers and make an informed decision.
"I’m most impressed with Tech Exactly’s ability to understand our challenges and come up with options to resolve them."
With other vendors I’ve worked with, I have to spend a lot of time explaining the challenge to them, and sometimes, they still don’t understand it. Tech Exactly takes the time to listen to us and offers us 3 – 5 different options to achieve the expected results.
Eric Shepherd
Foundation for Talent Transformation
“They are forthcoming, prompt, meticulous, sincere, punctual, and very professional. It's a joy to work with them!“
Akhil Chandra
Founder & Partner, Epiphany Labs
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Increase in free to paid subscriptions
“They’ve done a great job of meeting goals and deadlines as well as producing what was described in the scope of work.“
Kevin Eldredge
CAO, SSA Group
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Improvement in sales reconciliations timeline.
“They are so humble that even when the project is done, they always answer what we ask.“
Junie De Castro
World Fintech Festival Philippines
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Increase in user registrations and engagement
You will be in Good Care
We have worked with startups to multinational companies & we are well-versed in the challenges so relax
Frequently Asked Questions
It designs, builds and runs software that uses large language models or other generative models: chat and search over company data, document processing, AI agents and in-app copilots. The work covers model choice, data preparation, retrieval, evaluation, security and ongoing monitoring, not only the model call.
A proof of concept on your real data typically takes 2–4 weeks. Full production development ranges from 8–16 weeks depending on complexity: a straightforward chatbot is faster, and a multi-agent RAG system with enterprise integrations takes longer.
Start with retrieval-augmented generation in most cases. RAG keeps answers tied to your current documents and is cheaper to update. Fine-tuning helps when you need a consistent format, tone or specialized vocabulary that prompting and retrieval can't deliver, and it works best combined with RAG.
It depends on accuracy, latency, cost and where your data is allowed to go. During the proof of concept we test candidates such as GPT-6, Claude 5.5, Gemini 4 or an open-weight model on your actual data and pick on measured results.
Not with enterprise setups. The business API and cloud platform terms from OpenAI, Anthropic, Google, AWS and Azure exclude your prompts and outputs from model training by default. For stricter needs, open-weight models can run inside your own cloud account.
Yes. We use model endpoints covered by a BAA, redact or tokenize PHI before prompting, log access and keep a clinician in the loop for anything that affects care, with the controls documented for your security and compliance reviewers.
Yes. LLM integration into existing CRMs, ERPs, healthcare platforms and customer-facing apps is a core service. We add an API layer that calls the model, retrieves your data and enforces the same permissions as the rest of your app, starting with one feature and expanding once it proves itself.
Yes. We work with Boston teams, as a generative AI development company in Newton and the rest of New England, and we provide generative AI development services in New York, California and across the USA, fully remote with US time-zone overlap. Boston's biotech, life sciences and research teams in particular need compliant, production-ready AI.
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