Questions, answered honestly.
How Kevadia works, what we build, how we price, and what to expect — plus the common questions about each of our services.
Working with Kevadia
Where is Kevadia based, and do you work remotely?
Kevadia Innovation Studio is a New Jersey-based LLC and works with clients across the United States. Engagements run remotely by default, with on-site time where a project genuinely needs it. All engineering is done by US-based team members.
How much does a project cost?
Every engagement is scoped individually — there is no per-seat pricing or fixed package. After a short scoping call we give a written range tied to the actual work, and we will tell you early if budget and scope don't line up. Builds are typically fixed-scope; advisory and ongoing work run on a retainer.
What engagement models do you offer?
Three: partnership (a long-term embedded systems team across releases), consulting (a scoped build, architecture audit, AI system, or senior second opinion), and investment conversations. Public-sector clients can also engage directly, as a subcontractor under a prime, or as embedded advisory.
Who actually does the work?
The engineer who scopes your project is the engineer who builds it — Harsh Kevadia, with 10+ years at Meta and Amazon shipping systems for billions of users. There is no account layer and no handoff to a junior team; you talk to the person whose name is on the commit.
How quickly will I hear back?
Every inquiry is read by the founder and answered within 24 hours — with an honest read on whether and how we can help, even when the honest answer is a referral elsewhere.
Is Kevadia certified for government work?
Yes. Kevadia is certified by the State of New Jersey as both a Small Business Enterprise (SBE) and a Minority Business Enterprise (MBE), is registered on SAM.gov, and is self-certified as an SBA small business. W-9 and basic procurement documents are available on request.
Do I own the code, or is there lock-in?
You own everything. Every engagement ends with documented, tested code, runbooks, and handoff sessions so your team can operate the system without us. We build on mainstream stacks specifically so there is no lock-in by design.
How do we get started?
Send one message through the contact form describing what you're building. You'll get an honest reply within 24 hours, and if there's a fit we set up a scoping call to define what 'done' means before any code is written.
Custom Software
What kinds of software does Kevadia build?
Kevadia builds web applications, mobile apps, backend systems, and APIs — both greenfield products and modernization of existing systems. Typical engagements include SaaS products, customer portals, realtime systems, and platform rebuilds. Every project is scoped and built by a senior engineer, not handed down a chain.
How long does a typical build take?
A focused production build typically runs eight to sixteen weeks depending on scope: a clear spec in the first one to two weeks, working increments every week after, and a hardening pass before launch. We give a real range after the first scoping call — and we'll say so if your timeline isn't achievable.
Can you take over or modernize an existing codebase?
Yes. We start with an audit — architecture, data flows, deployment, the riskiest corners — then modernize incrementally using the strangler pattern so the product keeps shipping while we replace what's underneath. Big-bang rewrites are almost always the wrong call, and we'll tell you when they are.
How is working with Kevadia different from a typical agency?
There is no account layer. The engineer who scopes your project is the engineer who builds it — one with 10+ years at Meta and Amazon shipping systems for billions of users. You get fewer meetings, faster decisions, and code from someone whose name is on the commit.
What happens after launch?
Every build ends with documentation, runbooks, observability, and handoff sessions so your team can operate the system without us. After that, we stay available for support retainers or on-call advisory — but the system is yours, with no lock-in by design.
AI Automation & Agents
What is an enterprise AI agent?
An enterprise AI agent is software that uses a large language model to complete multi-step business tasks: reading context, calling tools and APIs, and acting within defined guardrails. Unlike a chatbot, an agent owns an outcome — resolving a ticket, reconciling a record — not just a conversation.
How long does it take to build a production AI agent?
A focused production agent typically takes six to twelve weeks: roughly two to map the workflow and define evals, four to six to build and iterate, and the remainder hardening for deployment. Timelines stretch when data access is unresolved, so we settle that in week one.
How do you prevent hallucinations?
Structurally, not with prompt wording. Agents retrieve from your verified data instead of relying on model memory, cite their sources, refuse when confidence is low, and are tested against regression suites that measure factual accuracy before and after every change.
Should we buy an off-the-shelf AI tool or build?
Buy when a vendor's workflow matches yours exactly; build when the agent must work inside your data, permissions, and edge cases. Most of our engagements start where an off-the-shelf pilot stalled. We'll tell you on the first call if buying is the cheaper answer.
Which models do you use?
We're model-agnostic and benchmark against your actual tasks: frontier models like Claude or GPT for reasoning-heavy work, smaller or open-weight models where latency, cost, or data residency demand it — with an eval harness that makes switching models a measured decision.
Data Platforms
What does a data platform engagement include?
A typical engagement covers an audit of your current pipelines, a target architecture with explicit data contracts, hands-on build of the new platform, and a staged migration with parallel runs. You end with infrastructure your own engineers can operate — plus runbooks and observability, not a slide deck.
Do we need petabyte scale to justify this?
No. Most clients come to us at terabyte scale with petabyte ambitions. The value of high-scale patterns is that they fail gracefully and grow without rewrites. We size the architecture to your next order of magnitude, not to Meta's — and we'll say so when simpler is better.
Can you migrate our data platform without downtime?
Yes. We migrate incrementally using the strangler pattern: new pipelines run in parallel with old ones, outputs are reconciled automatically, and traffic cuts over source by source once the numbers match. Dashboards and downstream consumers keep working throughout.
What stack do you recommend?
It depends on your workloads, but our defaults are Kafka for streaming, Spark for heavy transformation, Snowflake or a lakehouse for analytics, Postgres for serving, and dbt for modeling. We recommend boring, proven technology and spend the innovation budget on your product.
Our cloud data bill keeps growing. Can architecture fix that?
Usually, yes. Most runaway data spend traces to a few patterns: unpartitioned scans, duplicate pipelines, oversized always-on compute, and storage formats that fight the query engine. An architecture pass typically finds savings in the first audit week, and the redesign locks them in structurally.
Internal Tools
When is it worth building an internal tool instead of using SaaS?
Build when the workflow is core to how your business operates and off-the-shelf tools force workarounds — re-keying data, exporting to spreadsheets, or paying per-seat for features you don't use. If a SaaS product genuinely fits, we'll recommend it; the audit is honest either way.
How long does an internal tool take to build?
The core workflow of a typical internal tool ships in four to eight weeks. We deliberately start with the single highest-friction process, get it live with real users, then expand. Small, fast wins beat a six-month platform project that nobody has used yet.
Can you integrate with our existing systems?
Yes — that's usually the point. We integrate with CRMs, billing systems, data warehouses, payroll, and internal APIs so information is entered once and flows everywhere. Where a system has no API, we've built importers, parsers, and sync jobs that bridge the gap safely.
Who maintains the tool after it ships?
Your team can. We hand off documented, tested code with runbooks and admin controls, built on a mainstream stack your engineers already know. If you'd rather not own maintenance, we offer support retainers — but the tool is built so you're never locked in.
Technical Advisory
What does a technical advisory engagement look like?
Most start with a fixed-scope audit: one to three weeks reviewing your architecture, code, and operations, ending in a written assessment with prioritized recommendations. From there, teams either execute internally, retain us on call, or have us embed to lead the highest-risk piece.
Can you act as a fractional CTO?
Yes, for early-stage teams that need senior technical leadership before they can hire it full time. That typically means owning architecture decisions, running hiring loops, setting engineering process, and representing technology to investors — a few days a month, with clear boundaries.
Do you do technical due diligence for investors?
Yes. We assess the target's architecture, code quality, team, scaling risks, and AI claims, and deliver a written report in investor language: what's real, what's fragile, what it costs to fix. Typical turnaround is one to two weeks depending on access.
How is your advice different from a consulting firm's?
It comes from an engineer who still builds, not a practice that bills by the deck. Recommendations are grounded in reading your actual code and incident history, written so your team can execute them — and if the honest answer is 'don't hire us, do this instead,' that's the answer you get.