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Service · 06
AI Software Development
Production AI features embedded in your product—not demo chatbots. LLM orchestration, RAG pipelines, evals, and guardrails built into Next.js, Python, and Node stacks you can ship and maintain.
Fixed scopeAfter discovery call
At a glance
Who we serve, what we deliver, what happens next
Who we serve
Product and engineering leaders adding LLM-powered workflows, copilots, or retrieval to existing apps—or building AI-native SaaS from scratch.
What we deliver
Architecture, implementation, and hardening: prompts, tool calling, RAG, observability, cost controls, and human-in-the-loop review where it matters.
What happens next
Share your use case at /connect or book /schedule—we return a scoped plan, stack choices, and timeline.
- Base
- Chennai, India (IST) · remote-first
- Stack
- Next.js, Python, Node, vector DBs
- Models
- OpenAI, Anthropic, open weights via routing
- Engagement
- Discovery → fixed scope or sprint retainer
Overview
AI that survives production traffic
Shipping an LLM demo is easy. Shipping AI that handles bad inputs, respects permissions, stays within budget, and fails gracefully when a provider hiccups—that is software engineering. HiMat Technologies builds AI features the same way we build web platforms: scoped delivery, readable code, tests where they matter, and documentation your team can extend.
We work across retrieval-augmented generation, agent tool use, classification and extraction pipelines, and human review queues. Model choice is a product decision: we help you pick routing, fallbacks, and evaluation sets so you are not locked to a single vendor narrative.
Based in Chennai and working remote-first with clients worldwide, we align standups and async updates to IST-friendly windows while keeping delivery continuous across time zones.
Capabilities
What We Offer
Capabilities tailored to your goals
01
LLM Orchestration & Routing
Multi-model routing, retries, structured outputs, and cost caps—so one slow provider does not take down your workflow.
02
RAG & Knowledge Bases
Chunking, embedding pipelines, hybrid search, and citation-friendly answers grounded in your docs—not the open web.
03
Agents & Tool Integration
Safe tool calling against your APIs, CRM, or internal systems with auth, allowlists, and audit logs.
04
Guardrails & Evals
Input validation, PII handling, regression eval suites, and red-team checks before you widen access.
05
Copilots in Your UX
In-app assistants, draft-and-approve flows, and admin consoles that match your brand—not a generic chat widget.
06
Performance & Cost Control
Caching, batching, streaming UX, and token budgets so AI spend scales with revenue—not surprise invoices.
Process
How We Work
01
Use-Case Discovery
We map jobs-to-be-done, data sources, failure modes, and compliance constraints before picking models or frameworks.
02
Architecture & Eval Plan
Data flows, tool boundaries, eval datasets, and success metrics—signed off before implementation sprints.
03
Build & Instrument
Feature delivery with logging, tracing, and feedback hooks so you can improve prompts and retrieval with real usage.
04
Test & Harden
Automated evals, load checks, and security review on secrets, scopes, and user data paths.
05
Launch & Iterate
Gradual rollout, monitoring dashboards, and a backlog for model upgrades without rewriting the product.
Advantage
Why HiMat
01
Full-Stack, Not Slide Decks
We ship in your repo—API routes, workers, admin tools—not isolated notebooks that never reach production.
02
Security by Default
Secrets management, least-privilege API keys, and clear data retention policies for prompts and embeddings.
03
Honest Timelines
We quote after discovery. Pilots and vertical slices beat vague “AI transformation” retainers.
04
Remote-First from Chennai
IST-based coordination with async docs and recorded demos so global stakeholders stay aligned.
Stack
Technologies & Tools
Next.jsTypeScriptPythonFastAPINode.jsOpenAI SDKLangChain / custom orchestrationPineconePostgreSQLRedisVercel / AWSOpenTelemetry
Frequently asked questions
Related insight
How multi-agent systems help startups ship AI features without losing control.
Ready to ship AI in your product?
Tell us what users should accomplish with AI—we will respond with architecture options and a scoped proposal.
Start a conversation