AI development that ship
Practical AI for products—LLM features, copilots, RAG, automation, and MLOps—designed, built, and integrated by senior engineers in Bangalore alongside your web and mobile teams.
Generative AI & copilots
Embed assistants, summarization, search, and workflow automation into your app—with guardrails, observability, and cost controls your product team can own.
- ✓ OpenAI, Azure OpenAI, Anthropic, and open models
- ✓ RAG over your docs, tickets, and catalog data
- ✓ UX patterns users actually understand
ML & data pipelines
When off-the-shelf APIs are not enough—we help with feature engineering, training workflows, batch inference, and pipelines that fit your cloud and compliance needs.
- ✓ Python / Node inference services
- ✓ Vector stores and feature stores
- ✓ Monitoring drift and model performance
Secure delivery
AI that respects privacy, tenancy, and audit requirements—PII handling, access control, evaluation suites, and human-in-the-loop where regulations require it.
- ✓ Threat modeling for AI features
- ✓ Prompt and output logging policies
- ✓ Red-team style eval before launch
Three ways to partner
Product-first
AI features tied to real user journeys—not science projects.
Senior-led
Engineers who have shipped web, mobile, and data products before adding AI.
One partner
Build the app, integrate AI, test, and operate with ThiDiff end to end.
What we deliver
LLM integrations
Chat, search, and task automation wired to your APIs, auth, and analytics.
RAG & knowledge
Ground models in your docs, SKUs, policies, and support history with fresh indexes.
Agents & automation
Multi-step workflows—triage tickets, enrich CRM records, generate reports on schedule.
MLOps & observability
Tracing, evals, cost dashboards, and release gates so AI behaves in production.
AI in your stack
Plugins for ecommerce, support desks, internal tools, and mobile apps you already run.
AI QA & evals
Regression suites for prompts, golden datasets, and human review loops before go-live.
How we deliver
Discover
Use cases, data sources, risk, and success metrics—then a thin-slice prototype to validate value.
Design & build
UX, APIs, prompts, and backend services in agile sprints with demos you can share.
Evaluate & harden
Safety checks, load tests, cost caps, and QA on AI outputs—not just traditional functional tests.
Launch & improve
Ship behind feature flags, monitor quality, and iterate on prompts and retrieval monthly.
Questions? Answered.
Do you only build chatbots? +
Can you use our existing cloud and models? +
How do you handle sensitive data? +
Can AI work be combined with your dev and QA teams? +
Ready to add AI to your product?
Talk to usWhat you get
- ✓ Use-case workshop and feasibility assessment
- ✓ Senior engineers—not experimental-only contractors
- ✓ Build + integrate + evaluate under one partner