Why one LLM isn't enough: routing prompts across models without losing control
Model quality changes every month. Here's how we design routing, fallbacks and cost caps so your product never depends on a single AI vendor.
We build production-grade AI — agents, assistants, prediction models and multi-model systems — that plug into your workflows and pay for themselves in hours saved and revenue gained.

Built with the technology trusted by the world's best product teams
Good work shows up on the P&L, not just in the demo. These are the outcomes we design toward on every ai development engagement.
Discuss your projectPick one capability or hand us the whole problem — every service below is delivered by the same senior team that scoped it.
Agents that plan, call your tools and complete multi-step tasks, with approvals wherever risk is high.
Copilots and content tools grounded in your documents, products and tone of voice.
Retrieval pipelines that answer from your own knowledge base with sources, not guesses.
Send each request to the best model for cost, speed and quality — the same architecture behind our in-house AI workspace.
Forecast demand, churn and risk from your historical data and act before problems land.
Image and document understanding for quality checks, KYC, cataloguing and search.
A clear roadmap: which use cases to build, buy or skip, with expected ROI for each.
Guardrails, evaluation suites, audit logs and cost caps so AI stays safe and predictable.
Real products, real numbers — work we built or ran ourselves.
Startups get speed and focus. Growing companies get structure and scale. Established businesses get modernisation without disruption. Same team, adjusted to where you are.
Six phases, each with a clear output you sign off on — so budget, scope and quality stay visible from day one to launch and beyond.
Workshops to pin down users, outcomes and constraints. You get a scoped backlog, risks and a fixed or ranged estimate.
User flows, wireframes and a clickable prototype tested with real users before a line of production code.
Stack, data model, integrations and security decided up front — documented so any engineer can pick it up.
Two-week sprints with a working demo every sprint. Shared board, shared repo, no black boxes.
Automated and manual testing, performance and security checks, then a staged rollout with monitoring.
Post-launch SLAs, analytics reviews and a roadmap for the next release — we stay until it's working.
We pick proven tools for the job — not whatever is trending — and document every choice so your team can own it later.
Our in-house AI workspace runs on the same routing, evaluation and cost-control layers we deploy for clients.
Every AI feature starts with a measurable target — time saved, tickets deflected, revenue lifted.
We test against your real data and edge cases, then monitor quality in production.
OpenAI, Claude, Gemini or open-source — chosen per task, swappable later.
PII redaction, regional hosting and zero-retention options where your data demands it.
Documented prompts, pipelines and dashboards your team can own and extend.
| Engagement model | Best for |
|---|---|
| Fixed-scope project | MVPs and well-defined builds |
| Dedicated team | Long-term product development |
| Growth retainer | SEO, content and paid acquisition |
| AI sprint | Prototyping an AI feature in 2–4 weeks |
| Staff augmentation | Adding senior engineers to your team |
Behind every review is a business problem solved — a funnel leaking money, a site too slow to rank, a team drowning in manual work. Here's how clients describe working with us. Names are withheld to respect client confidentiality.
Spend went up only when the numbers justified it. Tracking was rebuilt properly before we scaled, and the weekly reviews were blunt and genuinely useful. We grew four times over without losing control of margins.
Read the case studyThe publishing stack and SEO playbook changed how quickly our stories get found. The team understood newsroom pressure, not just code, and breaking news now goes live in minutes.
Read the case studyThey pushed back on features that didn't matter and shipped the ones that did. The routing layer they built saved us from betting everything on a single AI vendor.
Read the case studyOur team used to open dozens of analytics tabs every morning. Now we see every site, live, in one place — and the browser extension is the first thing our editors check.
Read the case studyThe AI publishing engine replaced hours of copy-pasting. Live progress for every job means we always know exactly what went out, and where.
Read the case studyThe website shows our work beautifully on phones, and enquiries come straight to us instead of through marketplaces that take a cut.
Read the case studyQuick answers to what founders and product leaders usually ask us first.
OpenAI, Anthropic Claude, Google Gemini and leading open-source models. We often combine several and route each task to the best fit.
No. We use enterprise APIs with zero-retention options or self-hosted models, and keep sensitive data inside your cloud.
A focused prototype takes 2–4 weeks. Production rollouts with integrations and evaluation typically take 6–12 weeks.
We agree metrics up front — accuracy, time saved, deflection rate, cost per task — and build dashboards to track them live.
Field notes from building AI products, engineering publishing backends and running growth for our own brands and our clients'.

Model quality changes every month. Here's how we design routing, fallbacks and cost caps so your product never depends on a single AI vendor.

The technical SEO, publishing cadence and internal-linking habits behind a content network with millions of monthly readers.

A practical framework for scaling ad budgets on real numbers — contribution margin, payback period and creative fatigue.
Tell us what you're building. You'll get a reply from a senior engineer — not a sales script — within one business day, with a suggested approach and a ballpark.
Mon–Sat, 9:00 am – 8:00 pm IST
4th Floor, Cyber Towers,
HITEC City, Madhapur,
Hyderabad, Telangana 500081
MG Road, Labbipet,
Vijayawada,
Andhra Pradesh 520010
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— Mon to Sat, 9am–8pm IST