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Scope an AI Pilot →For Agencies Talk to Us

AI that does the work
and shows its sources.

AI development services that do real work for your business. Chatbots answer from your own documents. Automation clears repetitive tasks. Knowledge systems cite every answer. We build on the tools you already run and start with a working pilot. Nothing is hidden: you see the prompts, the test results and the source behind every answer.

Get a ProposalGet a Free AI Automation Review

Reply within four business hours (typical) · No platform lock-in

Brands our teams have delivered for

  • Hello Peter
  • Gruber Logistics
  • Delhivery
  • Thomson Reuters
  • Qatar Airways
  • Grundfos
  • Save
  • BERD
  • Yale University
  • Kuwait Police
  • Dubai Police
  • Panasonic
  • Infosys
  • Kia
  • Hitachi
  • Orange Business Services
What we do

PixelCrayons builds AI chatbots, workflow automation, knowledge systems and personalisation on your existing stack. Every project starts with a small pilot: one workflow, your data and a working result. Safety limits, testing and handover are included. Anything that shouldn't run on its own keeps a person in the loop. We work direct for brands and white-label for agencies.

  1. Discovery & scoping, in writingOne workflow mapped, its data audited and a correct result defined before anything is built.
  2. Built on your stackBuilt on the cloud, CRM and helpdesk you already run, with models you can swap.
  3. Safety limits and testingTests built from your real cases, checks against your documents and a hand-over to a person when unsure.
Our work

See what we've built
and the results it brought.

Real projects for real clients, with results we can show.

All case studies →
2004
Established
500+
Agencies served
4,500+
Projects delivered
340%
Revenue growth · 7 months
eCommerce
+127%
Organic traffic · 5 months
SaaS
85%
Faster delivery · backlog cleared
via agency partner
Clutch rating 4.9 / 5, checked 15 September 2026Read our GoodFirms reviews
Google Partner
Shopify Partner
Where the work happens
ShopifyWooCommerceMagentoWordPressWebflowKlaviyoGoogle AdsMeta AdsGA4Next.js
  • Reply within four business hours (typical)
  • Clear IP & Ownership Terms
  • Grounded answers: sources shown
  • Human handover built into every assistant
  • Your stack: no forced migration
  • Delivering since 2004, before and after the AI wave
Pick your starting point

Choose where to start
with AI.

Most projects start with one pilot, such as a chatbot, an automation or a knowledge base. They grow once the pilot has proved its value. We pick a pilot with a measurable volume of requests, so you see its value before anything larger is scoped.

01AI ChatbotsSupport and sales assistants that answer from your documents and show their sources. They hand over to a person when unsure.02Workflow AutomationSorting requests, drafting replies, data entry and reporting handled automatically. People stay in the loop for the judgement calls that matter.03Knowledge / RAGSystems that find the right passages in your own documents (policies, manuals, past tickets) and answer from them. Your team stops hunting through folders.04PersonalisationRecommendations, search and on-site content shaped by what customers really do, and measured against a control group rather than guessed.05AI AgentsSoftware that plans and takes several steps toward a goal, using your tools. Anything that can't be undone waits for a person's approval.06Hire AI TalentVetted AI engineers who join your daily meetings when you'd rather own the build: your tools, your process, weekly sprints.

Looking to be cited by ChatGPT, not to build with it?

That is a different job. We structure your site so AI answer tools can quote it, with sources pointing back to your pages. It needs content, schema and authority work, not a model. That's why it sits under marketing. One published SaaS case earned AI Overview citations alongside 127% organic traffic growth (single engagement).

AI search services
In every engagement

What an AI build
actually includes.

01

Discovery & scoping, in writing

First we map the one workflow worth automating. We check the data and systems it touches and agree what a correct result looks like, before anything is built. Discovery also answers a question most vendors skip: should you build at all? The pilot you approve is small enough to prove its value in weeks. It is itemised enough to hold us to.

Week zero
02

Built on your stack

You don't have to move platforms. We build on the cloud, CRM and helpdesk you already run. We choose models on fit, cost and where your data must be stored. You can swap the model underneath without rework when better or cheaper options appear. That happens every few months.

Every build
03

Safety limits and testing

Every assistant comes with a set of tests built from your real cases. Its answers are checked against your documents. When it is unsure, it hands over to a person instead of guessing. Logs let you check what happened afterwards. If it doesn't know, it says so. One wrong guess in front of a customer costs more trust than many right answers earn back.

Before launch
04

Integration with existing systems

The pilot plugs into the tools your team already uses: helpdesk, CRM, Slack and internal APIs. Nobody has to change how they work to use it. If a system has no API, we find another way to connect it. That is the skilled part of the job.

Included
05

Handover & training

You get documentation, admin training and a runbook (a written guide) your team can use without us. It shows how to update the knowledge base, read the test reports and change the hand-over rules. Your materials remain yours. Bespoke deliverable rights, licences and handover are agreed before work starts. No lock-in, no black box, and no need for us to keep it running.

At handover
How it starts

How an AI project starts,
from brief to first delivery.

01
Start

Brief and a call

We sign an NDA and talk through the workflow worth automating first and the documents and systems it touches.

02
Once the brief is complete

Itemised proposal

We confirm the date your proposal arrives. It covers one workflow, real data, named safety limits, a demo date and the itemised price.

03
Your decision

You sign off

You confirm the scope, the payment and the access we need. Nothing starts before this.

04
Typically 2 to 3 business days later

The team starts

We audit the documents and systems the workflow touches and agree in writing what a correct result looks like.

05
On the date in your proposal

First deliverable

A working pilot that answers from your own documents. Next it runs against real cases and connects to your helpdesk and CRM. Your team is trained on the runbook.

Inside Prism

Your engagement, week to week,
in one workspace.

Prism is the client workspace where your requests, approvals, tasks and weekly reviews live.

Some engagements include Prism, our client workspace, and your proposal says whether yours does. Where it does, your AI build runs in a workspace you log into: requests, approvals, the task list and the weekly review, with each decision and its expected result written down.

See how Prism runs an engagementGet a Free Website Review →
  • 01

    Requests and approvals, in one place

    Raise a request in your workspace, approve a piece of work, and see who owns it and when it is due.

  • 02

    Owned tasks and routines

    Every task has one owner and a date. Recurring work runs as a routine, so nothing depends on someone remembering.

  • 03

    A weekly review with decisions recorded

    Each decision is written down with the expectation attached: what we expect to change, and by when.

  • 04

    Every action recorded, checked against the outcome

    What we did and what happened sit side by side, so the next review starts from evidence rather than memory.

How we report it, in Prism

The eval scorecard,
before the pilot goes near a customer.

What you receive in month one

AI work is reported against an evaluation set built before any model is chosen. In the first month you receive the task definition with the inputs and acceptable outputs written down, the eval set of real cases with expected answers, and the scorecard showing accuracy, refusal behaviour and cost per run. The go/no-go checklist names what must hold before the pilot touches live traffic.

  • 01Task definition: inputs, acceptable outputs, and the cases the system must decline
  • 02Eval set: real cases with expected answers, reviewed by your team
  • 03Scorecard: accuracy, refusal behaviour, latency and cost per run
  • 04Go/no-go checklist: the thresholds the pilot must meet before launch
  • 05Failure log: each wrong answer, its cause, and the fix applied

Related workB2B SaaS: from unseen to cited in AI answers.SaaS · UK · A different discipline, so it is linked here rather than presented as proof of this one.

Beyond AI

Marketing, development, design and AI from one senior team

One team builds the chatbot, the site it lives on and the search visibility that brings visitors, on one plan. Agencies can resell all of it white-label.

Marketing servicesDevelopment servicesFor agencies
Industries

Industries we know well,
and the problem each one faces first.

Our services are the same in every sector. What changes is the problem to solve first. Here are four industries we know well, and the rest of the list.

SaaS & Tech

Traffic reports look healthy while your pipeline stays flat. Buyers now ask ChatGPT and AI Overviews before they compare suppliers. We offer pipeline-first search, AI-answer visibility, product-led content and product UI, measured in signups and pipeline.

How we work in SaaS

Funded Startups

You've raised money, your roadmap is public and the clock is running. We are one senior team for web, design, brand and AI. We deliver fast, without the rewrites, the pile of suppliers or the scope creep that eats runway.

How we work in Startups

Healthcare

Winning patients while staying compliant: careful builds, local search visibility for every location, and a reputation managed with the care the sector demands.

How we work in Healthcare
Also servingEducationReal Estate & ConstructionDentalHome ServicesAll industries →
Who is accountable

The people responsible
for your work.

Leadership and how we’re built →
Parvessh Agarwal

Parvessh Agarwal

Founder & CEO

An entrepreneur at heart. He links business analysis, strategy, clear goals and ROI to practical technology.

LinkedIn →
Saundaraya Gupta

Saundaraya Gupta

Technical Manager

Brings technical work, client updates and project management together, so work moves smoothly from brief to launch.

LinkedIn →

Every engagement

A named coordinator and escalation contact

Know who coordinates your engagement, who owns the work and how to escalate an issue.

All engagements. Roles may be combined and vary with your engagement.

Full terms →
Before you sign

Our commitments

Each one says where it applies and links to its full terms.

Response and start times

We typically respond within four business hours. Eligible engagements can typically start within two to three business days after scope, payment and required access are confirmed.

Business hours are Monday to Friday, 9:00 am to 6:00 pm IST, excluding published company holidays. Typical expectations, not guaranteed service levels.

Full terms

Clear IP & Ownership Terms

Your materials remain yours. Bespoke deliverable rights, licences and handover are agreed before work starts.

All engagements.

Full terms

Clear Delivery & Escalation Ownership

Know who coordinates your engagement, who owns the work and how to escalate an issue.

All engagements. Roles may be combined and vary with your engagement.

Full terms

How we handle claims, credentials and your data: group credentials, dated ratings, how case figures are signed off, client permissions and data handling.

What discovery decides

Buy a tool, build a pilot,
or keep a person on it.

Discovery ends with a written recommendation, and sometimes it says not to build. These are the findings that decide which way it goes.

What discovery findsWhat we recommendWhy
The workflow is generic and an off-the-shelf tool can already reach your dataSubscribe to the tool, and the document says soA pilot that should not exist wastes your money and our reputation.
The workflow is core to how you make moneyA scoped pilot: one workflow, your own data, a working deliverableThis is where custom pays off. The pilot proves it before anything larger is priced.
Answers must come from your own documentationA grounded build that shows its sourcesEach answer can be checked against the passage it came from, and low confidence hands over instead of guessing.
The ready-made option cannot connect to the systems your team usesCustom, built on your existing cloud, CRM and helpdeskYour team shouldn't have to change how they work to use it. If a system has no API, we find another way in.
A step needs a judgement call, such as a refund outside the returns windowAutomate around it and route that step to a personThe assistant passes on the full thread and the relevant policy. It does not make the call.
Your data must not leave your infrastructureDeploy inside your own cloud account or private environmentRules for keeping, storing and accessing data are agreed in the scope document before launch.

Growing beyond the pilot is priced only after the pilot has proved its value.

Questions

Frequently
asked.

Less than most agencies imply, because we start with a small pilot: one workflow, your data and a working result. The proposal itemises what you get, including the integrations, safety limits, testing and handover. Growing beyond the pilot is priced only after the pilot has proved its value.

The ones that fit your data, your budget and where your data must be stored, chosen in discovery. We don't favour any one model. Each build lets you swap the model without rework as better or cheaper options appear. What matters more is how answers link to sources, how mistakes are caught and how it fits your tools.

It stays yours. Work runs under NDA, and your documents and customer data are used for your system and nothing else. Where needed, we deploy inside your own cloud or private setup. We use enterprise API terms under which providers don't train on your data. Rules for keeping, storing and accessing data are agreed in the scope, and access is logged.

Any language model can, so our job is to make errors rare, visible and safe. Every assistant answers from your own documents, with sources shown. When it is unsure, it hands over to a person. It's tested against your real cases before launch, and the logs let you check what was said and why.

Sometimes you should buy, and we'll tell you so in discovery. A ready-made tool makes sense when the workflow is common and the tool can reach your data. Custom pays off when the workflow is core to how you make money. It also pays off when answers must come from your documents, or no tool connects to your systems. Discovery ends with a written recommendation either way.

Whoever you choose: you're not locked in to us. Every build comes with documentation, admin training and a runbook your team can follow. IP and ownership terms are agreed before work starts. The usual choice is a light retainer for monitoring, test re-runs and changes, itemised in writing and cancellable. Or you run it in-house.

A working pilot, not a slide deck. That means one workflow, your own data and a working result, built on the tools you already run. Safety limits, tests from your real cases and a runbook for your team are included. Your materials remain yours, with deliverable rights, licences and handover agreed before work starts.

From the blog

Our latest writing
on AI.

All articles
AI tools for digital marketing: what to check before it ships
8 October 2026 · 10 min read

AI tools for digital marketing: what to check before it ships

AI tools for digital marketing now draft copy, set bids, pick placements and flag changes in your reports, much of it inside Google Ads, Meta and GA4.

AI visibility audit: how we measure mentions and citations on a frozen prompt set
6 October 2026 · 5 min read

AI visibility audit: how we measure mentions and citations on a frozen prompt set

An AI visibility audit records what assistants say about you, on fixed questions, under recorded conditions.

AI agent vs automation vs a chatbot: the questions we ask before building an agent
29 August 2026 · 5 min read

AI agent vs automation vs a chatbot: the questions we ask before building an agent

A chatbot answers, an automation follows a path drawn in advance, and an agent chooses its own next step.

The range

What it costs,
at the direct rate.

Each AI service has its own price row below, as a pilot and a retainer. The team suits you if you plan to use several of them and want one senior team, billed monthly.

  • RetainerAI engineering team$5,000–$20Kper month

Indicative: every figure is refined into an itemised proposal.INR figures shown excl. GST.

PricingSee indicative pricing for this serviceDirect and wholesale, in ₹ and $ →

Put AI to work on
one real workflow.

Scope a pilot: one workflow, your own data, a working deliverable with guardrails, evaluation and handover included, and a written recommendation if custom isn't the right call.

Get a ProposalGet a Free AI Automation Review

Reply within four business hours (typical) · NDA standard · Clear IP & Ownership Terms

Rankings on this topic

Scored on public evidence by the PixelCrayons Index. PixelCrayons is scored like every firm: ranked where it has a case study, listed where it has not.

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