Ask us the awkward ones

For MVPs and standard e-commerce projects, we usually launch within 3-5 weeks. Complex SaaS platforms or legacy modernizations are scoped out into phases to ensure continuous delivery.

We connect your applications to advanced models like GPT-4 or Claude via secure APIs, and build custom data pipelines for recommendation systems, chatbots, and automated workflows.

Yes. We use an incremental modernization strategy (the Strangler Pattern), slowly moving features to a modern stack (Next.js/Node.js) while keeping your old system operational and synced.

Security is built-in, not bolted on. We implement end-to-end encryption, OAuth2/OIDC for auth, and follow OWASP guidelines to protect your data from common vulnerabilities.

Yes, we offer monthly managed support packages that cover security patches, performance monitoring, and feature updates. We also provide a 30-day post-launch warranty on all work.

Our core expertise is in React.js, Next.js, Node.js, and TypeScript. For cloud, we are AWS and Azure partners, and we work with both SQL and NoSQL databases like PostgreSQL and MongoDB.

Shopify wins when you need to launch in days with a standard catalogue and checkout. A custom build wins when per-transaction app fees are eating your margin, when your pricing or bundling logic does not fit Shopify cleanly, or when performance and SEO are core to how you grow.

A full custom storefront with payments, cart, inventory and order tracking starts at ₹2L and typically ships in three to five weeks. Scope drives the number — the count of product types, the complexity of your pricing rules, and how many systems the store has to talk to.

Yes. We map every existing URL to its new destination, ship 301 redirects with the launch, preserve structured data and monitor Search Console for the first month so ranking drops get caught in days, not quarters.

We do — that is the point of having the growth lines in-house. The same team can run your SEO, Meta ads and social so the store launches with traffic pointed at it instead of waiting on an agency handover.

A focused MVP starts at ₹1.5L for a production-ready build with authentication, a database, the core flow, responsive design and deployment. The price moves with the number of core features and integrations, not with how ambitious the long-term vision is.

Yes, when the scope stays honest. Four weeks is plenty for authentication, a database, a few core flows and a clean responsive UI. It stops being realistic when the MVP quietly grows into three dashboards and a mobile app — so we lock scope in writing in week one.

You do, outright, from the first commit. The repository is yours, hosted under your account where you want it, with no licensing strings and nothing held back as leverage.

You start learning from real users. From there most founders move to a monthly retainer so the product keeps evolving, or pick up a dedicated developer to carry it forward in-house.

Dashboard and SaaS builds start at ₹1.5L for a production release with a custom UI, data visualisation, user and role management, reporting and API integrations. Subscription billing and multi-tenancy add scope, so we price those against your actual plan structure.

Usually yes, and it is worth doing deliberately rather than gradually. We audit the data model, pick row-level or schema-level isolation based on your compliance needs, and migrate in stages so the live product keeps working throughout.

Yes. Dashboards are only as good as the pipeline behind them, so we read from where your data already lives — Postgres, BigQuery, Snowflake or an internal API — rather than insisting on a new store.

A builder gives you pages. A custom application gives you logic — user roles, workflows, calculations, integrations and data that behave the way your business does. If a builder can do what you need, you should use one; we will tell you when that is the case.

Yes. We start with a short audit covering architecture, dependencies and test coverage, then propose whether to extend, refactor incrementally or replace a module at a time. We do not open with a rewrite recommendation.

Your call. Many clients move onto a retainer with us, some hire a dedicated developer through us to own it in-house, and some take the documentation and run it themselves. The handover is the same either way.

For large systems with dedicated platform needs, specialists win. For products up to a reasonable size, full-stack engineers ship faster because most features touch every layer, and a feature that needs three people to coordinate takes three times as long to get right.

TypeScript everywhere, React and Next.js on the front end, Node.js on the back, Postgres or MongoDB depending on the data shape. We will use something else when your team already runs it — your maintainability beats our preference.

Yes, starting with an audit of architecture, dependencies and test coverage, then a recommendation to extend, refactor incrementally or replace module by module. We do not open with a rewrite.

Almost always one of three things: a page builder generating enormous markup, too many plugins each loading their own CSS and JavaScript, or unoptimised images on shared hosting. All three are fixable, and we quantify each in the audit before recommending a rebuild.

A builder is fine if nobody technical will ever touch the site and speed is not a priority. If you care about Core Web Vitals or expect to grow, a custom theme is faster, cheaper to maintain and does not lock your content inside one plugin's shortcodes.

Headless keeps WordPress as the editing interface but renders the public site with Next.js, which is dramatically faster. It is worth it when speed or a complex front end matters; it adds cost and complexity you do not need for a simple brochure site.

Yes — cleanup, root-cause identification, hardening and a monitoring setup so it does not recur. Cleaning without finding the entry point just delays the next compromise.

Shopify if you want a hosted platform and your requirements are standard. WooCommerce if you need control over checkout and pricing logic, want to avoid per-transaction platform fees, or already run WordPress for content. We will tell you honestly which fits.

Woo stores product data across several WordPress tables, so filtering and search get expensive as products multiply. The fixes are object caching, a proper index strategy and sometimes a dedicated product lookup table — all solvable, but they need doing deliberately.

Yes — role-based pricing, quantity breaks, customer-group catalogues, quote requests and net payment terms. This is one of the main reasons businesses pick WooCommerce over a hosted platform.

Yes. Products, customers and orders migrate with a URL map and 301 redirects shipped alongside, plus Search Console monitoring for the first month so any ranking drop is caught in days.

REST for straightforward resource access and public APIs where caching matters. GraphQL when clients need wildly different shapes of the same data and you are tired of adding endpoints. Most products are well served by REST; we recommend GraphQL when the query pattern genuinely justifies it.

Usually, and the fix is almost always structural: no retries, no idempotency, and no alerting. We add all three, then backfill whatever was lost while it was failing quietly.

Often yes — via database replication, file drops, screen-level automation or a thin adapter service in front of it. We scope the least fragile option available rather than promising a clean one that does not exist.

Start with web unless your product genuinely needs the camera, background location, offline use or push notifications. Web is faster to ship, cheaper to change and has no review queue — and a progressive web app installs to the home screen for free.

A focused cross-platform app typically runs six to ten weeks of build. Because React Native shares one codebase across both platforms, you avoid paying twice for the same feature, which is where most native quotes get expensive.

Yes. Rejections are normal on a first submission, usually over privacy declarations or account deletion requirements. We prepare for the common ones up front and handle the back-and-forth when it happens.

That is what grounding is for. We retrieve from your own content and require the model to answer from it, with a scored evaluation set proving the accuracy rate before launch and an escalation path for anything it should not answer.

Model choice per task, prompt caching, retrieval that sends only the relevant passages instead of whole documents, and hard spend caps with alerting. Most of the saving comes from not using a frontier model for work a small one handles fine.

Yes, where it needs to. We can deploy open-weight models in your cloud for data-residency or compliance requirements, though hosted APIs are usually cheaper and better until volume is high.

Usually yes, and usually substantially. The common wins are right-sizing over-provisioned instances, moving cold data to cheaper storage classes, killing orphaned resources nobody owns, and putting caching in front of expensive queries. We start with an audit that quantifies each before changing anything.

Probably not. Most products are better served by a managed platform until team size and traffic justify the operational overhead. We recommend Kubernetes when it solves a problem you actually have, not as a default.

That is the common case. We map what is actually running, document it, then move it into code incrementally so there is no risky big-bang migration.

Yes, measurably. Industry studies consistently put the cost of each additional second of load time at roughly 7% of conversions, and Core Web Vitals are a confirmed Google ranking signal — so a slow site loses both the visitor and the position that would have brought the next one.

Lighthouse is a lab test on simulated hardware. Your users are on mid-range phones and real networks, and Google ranks on field data from actual visits. We optimise against the field numbers, which is why the two diverge.

Most of this work is on sites we did not build. WordPress, Shopify, custom React — the audit process and the fixes are the same, only the implementation route differs.

Bug fixes, security patches, dependency upgrades, monitoring, backup verification and a monthly block of hours you direct at features or improvements. Anything beyond the block is quoted separately before it starts.

Yes, after an onboarding audit. We need to read the code and document the risks first, because taking on-call responsibility for a system nobody understands is how outages happen.

Retainers are rolling monthly. You can pause or cancel with notice, and the documentation stays yours either way.

Technical fixes can move rankings within weeks. Content and authority work takes longer: expect early movement around month three and compounding results from month six. Anyone promising page-one rankings in thirty days is either buying ads or lying.

Retainers start at ₹35,000 per month, which covers technical work, on-page optimisation, a content allocation and reporting. The number moves with how many pages are in scope, how competitive your queries are, and whether we are also producing the content.

No, and no honest provider can — the ranking is Google's decision, not ours. What we commit to is the work, the baseline measurement and monthly reporting against clicks and positions, so you can see exactly what your spend is buying.

It matters more, and the work has widened. Answer engines cite sources, and they overwhelmingly cite pages that are already technically sound, clearly structured and well linked. We build for both: ranking in search results and being the page an AI quotes.

Yes — Google Business Profile optimisation, local citations, review strategy and location pages for businesses selling in specific cities or regions.

Regular SEO is mostly content and links. Technical SEO is whether search engines can reach, render, understand and prioritise your pages at all. A brilliant article on an unindexable page ranks nowhere, which is why this work comes first.

Yes, and quickly — post-migration drops are usually redirect mapping, canonical or indexation problems, all diagnosable within days. The faster you act the more recoverable it is.

It can. Client-rendered content may be indexed late or incompletely, and the common symptoms are pages indexed with no content or wrong titles. We test what the crawler actually receives rather than assuming.

We fix them. Because we are also the engineering team, the audit and the implementation are the same engagement rather than a handover to someone who deprioritises it.

Realistically no — proximity to the searcher is a dominant factor in map-pack results. You can rank organically for that city with a genuine location page, and anyone promising map-pack placement without a presence there is selling you something that will not work.

More than your map-pack competitors, acquired steadily rather than in bursts, and responded to. Recency and response rate both matter, not just the total.

Yes, with a location page per branch, a profile per branch and consistent data across all of them. Multi-location work is mostly a data-hygiene problem, which is good news — it is tractable.

Enough for the algorithm to learn, which in practice means a daily budget that produces at least 20–30 conversion events a week. Below that you are paying for noise. We size the test budget against your actual order value before recommending a figure.

Management starts at ₹30,000 per month plus your ad spend, which includes account structure, creative production, testing and reporting. Larger accounts move to a percentage of spend once the volume justifies it.

Usually creative fatigue — the same audience has seen the same ad too many times — or a tracking break after a site change. Both are preventable: we run creative on a refresh cycle and monitor event match quality so a broken pixel surfaces in days.

We produce it — static, carousel and short-form video — because creative volume is the main lever on Meta. If you have a brand team or existing assets, we work with those instead and focus on angles and testing.

Yes, and it is usually the highest-value thing we do first. Conversions API with server-side events, proper event deduplication and consent handling recovers most of the signal lost to browser-side-only pixels.

They run through the same Ads Manager, but treating them as one campaign with shared creative is the common mistake. Instagram placements need vertical, fast-hook creative; reusing a Facebook feed asset is why many accounts see Instagram underperform.

They are frequently the cheapest placement on Meta right now, because supply is high and many advertisers still do not produce vertical video. That advantage lasts only while that is true.

Not necessarily, though creator-style ads often outperform polished brand assets. Partnership ads let you run a creator's post from their handle, which usually beats the same content on a brand account.

Google if people already search for what you sell; Meta if you have to create the demand. A plumber starts with Google. A new snack brand starts with Meta. Most businesses eventually run both, with Google capturing intent and Meta generating it.

Usually competition on the head term plus a quality score problem. Broader match types and a landing page that does not match the query both raise what you pay. Tighter intent grouping and landing-page alignment are the normal fixes.

It works well with a healthy product feed and solid conversion data, and poorly as a substitute for either. We usually get Search and Shopping performing first, then layer Performance Max with brand exclusions so it does not just harvest traffic you already had.

Yes. A paid audit covers structure, tracking accuracy, wasted spend and quality score, and comes back as a prioritised list you can act on with or without us.

Packages start at ₹25,000 per month for strategy, 12–20 pieces of content, scheduling, community management and reporting. Video-heavy plans and extra channels cost more, since production time is the real driver.

The ones your buyers use, and no more than you can sustain. B2B usually means LinkedIn plus YouTube; consumer and retail usually means Instagram plus short-form video. Two channels done properly beats five done occasionally.

Yes — reels, shorts and cut-downs are produced in-house, either from footage you supply or from assets and screen capture we create. Short-form video is where organic reach still lives, so it is the core of most plans.

It can, when the content answers buying questions and the profile makes the next step obvious. We report on enquiries and profile clicks alongside reach, and treat follower count as a vanity metric rather than the goal.

Because most growth problems sit on the seam. A landing page that loads in five seconds wastes ad spend; a tracking change breaks attribution; an SEO recommendation needs a developer. When the same team owns the build and the campaigns, that handover — and the blame that comes with it — disappears.

Programmes start at ₹60,000 per month for management across channels, plus ad spend. The right total depends on your average order value and sales cycle — we build the growth model first and let it size the budget, rather than picking a number and hoping.

Paid channels produce data within two weeks and stable performance by month two. SEO and content compound from month three to six. We sequence the programme so paid funds early learning while the organic work builds.

Often, yes. We can run the whole funnel, or take the channels your team does not cover and plug into their reporting. The requirement is one shared definition of a conversion.

No, and a guarantee usually means unqualified volume — easy to hit and useless to sales. We commit to the system, the measurement and a cost-per-qualified-lead target we agree after the first month's data.

Usually the offer attracts the wrong person, or follow-up is too slow. Both show up immediately once leads are scored and response time is tracked, which is why those come before more spend.

Yes — HubSpot, Salesforce, Zoho, Pipedrive or a spreadsheet if that is genuinely what you run. The requirement is one agreed definition of a qualified lead, not a particular tool.

Enough for a result to reach significance in a reasonable window — in practice a few hundred conversions a month per variant. Below that, fix the obvious friction and page speed instead; testing with too little traffic produces confident nonsense.

Usually, and the two compound. Lifting conversion from 1.5% to 2% makes every existing and future click worth a third more, which lowers your acquisition cost on every channel at once.

Only if the evidence says so. Most gains come from a handful of targeted changes, and because we are also the engineering team, those get implemented rather than recommended.

Four well-researched pieces mapped to real queries beat twenty thin ones, every time. We usually start at four to six a month against a cluster plan, and increase only once the cluster is earning positions.

It leads with a direct answer, carries standalone claims an engine can lift without rewriting, uses real headings and structured data, and states facts the rest of the site also asserts. Those are the pages that get cited rather than summarised away.

Yes — that is the easier case for us, because the engineers are in the same building. Technical content gets reviewed by someone who has actually built the thing before it ships.

Yes. Content without a capture and nurture path just rents attention. We set up the sequences, segmentation and reporting alongside the content programme.

A freelancer is a contract between you and one person, with their availability, their vetting and their absence as your risk. A dedicated engineer through us comes vetted, is managed by an engineering lead, has a replacement guarantee behind them, and keeps working when someone falls ill.

From ₹1.2L per month for a full-time senior engineer, all-in — no recruitment fee, no equipment cost, no payroll overhead. Rate varies with seniority, stack and how much timezone overlap you need.

You should, and you do. We shortlist, you interview, you choose. Then there is a two-week paid trial inside your actual workflow before anyone asks you to commit beyond it.

You tell us, and we replace them. The trial period exists precisely so that decision is cheap, and the replacement's ramp-up is on us rather than on your budget.

We work with teams across IST, GMT, CET and US hours, with at least four hours of daily overlap as standard and full-shift overlap available. Overlap is agreed in the role brief, not discovered later.

You do, entirely. Work is done in your repositories under your accounts, covered by an IP assignment and NDA signed before anyone starts.

From ₹1.2L per month for a full-time senior engineer, all-in — no recruitment fee, no equipment, no payroll overhead. Rate varies with seniority and how much timezone overlap you need.

A realistic component build covering state, data fetching, re-render behaviour and accessibility, plus a conversation about rendering strategy and performance. Algorithm puzzles tell you almost nothing about whether someone writes maintainable React.

That is the normal case. They join your repo, your linting rules and your review process, and the first week is deliberately about reading before writing.

Most can model data and write efficient queries; fewer can tune a database under load. We ask explicitly in the role brief so the shortlist matches what you actually need rather than what the title implies.

NestJS, Fastify and serverless patterns are all common in the pool. We match to whatever you already run rather than imposing a framework preference.

Some are comfortable owning CI/CD and infrastructure, which we flag during vetting. If infrastructure is the real need, a dedicated DevOps engineer is usually better value than a back-end engineer doing it part-time.

At the extremes of either discipline, yes. For a product team shipping features that touch every layer, a competent full-stack engineer ships considerably faster than two specialists coordinating — because the coordination is the expensive part.

From ₹1.3L per month for a full-time senior engineer, all-in. Slightly above a single-discipline engineer, and usually cheaper than the two hires it replaces.

When one layer becomes a full-time job on its own — heavy data engineering, a large design system, or infrastructure at scale. We will tell you when you have reached that point.

When the work is a whole workstream rather than extra hands — a new product area, a platform migration, a mobile app alongside the web product. A pod comes with its own lead and QA, so you are buying delivery rather than managing individuals.

Same tracker, same repo, same definition of done, plus a sprint demo you attend. The technical lead reports velocity and risk honestly, including the bad sprints — a status that is always green is a reporting problem, not a delivery success.

Overlap hours are agreed before the pod starts, with a minimum of four hours' daily crossover as standard. Written-first communication means progress does not depend on catching someone live.

Yes, starting with an audit and a documented onboarding period. We would rather spend two weeks understanding what exists than six months discovering it.

When technical decisions are outrunning the team's experience but the burn cannot carry a full-time CTO — typically a non-technical founder with a small dev team, or a company about to raise and facing due diligence.

Only if it is genuinely the right answer, and we will say plainly when it is not. The advisory engagement is priced on its own so the advice does not have to sell anything.

Yes, on either side. Findings cover architecture, code quality, security posture, key-person risk and the real cost of the roadmap, delivered as a report the deal team can use.