Perform Digital, since 2019

AI agents that show their work.

For over seven years Perform Digital has built data, marketing and AI systems that organisations rely on. Today we build AI agents for colleges, clinics, software teams and public offices, with the context they read and the limits they work within.

See the work

One request, followed from question to sign-off

  1. Asked

    “I missed the application deadline by two days. Can I still apply?”

    Applicant, admissions chat, 23:12

  2. Read

    • Admissions policy§3.1 Late applications
    • Fee schedule§4.2 Late fee

    Ranked context, each source cited

  3. Did

    Found the applicant’s saved form in the admissions portal and drafted a reply with the late route and the fee.

    Admissions portal, read only

  4. Checked

    Act with approval

    Held for the admissions officer, who approved it. Sent at 09:05.

An illustrative example. The agents we build log every action with its sources, so a person can check it. How autonomy is set

The shift

The web has a new reader.

For thirty years websites, forms and back offices were built for people. Now the busiest visitor is often software acting for someone. Businesses that agents can read are easier to find, compare and choose.

Already here

Software reads first

Assistants and answer engines read your pages, prices and policies before a person ever arrives, and summarise you for them.

Over halfof Internet traffic in 2026 was not human, for the first time.Cloudflare, The Internet has a second audience, 30 Sep 2026

Arriving

Agents act

They compare suppliers, book, apply and buy on someone’s behalf, through forms, APIs and protocols built for them.

75%of B2B purchase decisions will be influenced by AI agents in 2027.Forrester, 2027 B2B go-to-market predictions, 21 Oct 2026

Ahead

Agents run the routine

Inside companies and departments, agents take intake, scheduling, checks and drafting, while people approve what matters.

80%of governments will deploy AI agents to automate routine decision-making by 2028.Gartner prediction, 17 Mar 2026

Where agent projects break

Gartner expects over 40% of agentic AI projects to be cancelled by the end of 2027.

Gartner points to cost, unclear value and weak risk controls. In practice agents struggle when they read stale or conflicting context, act without clear limits, or cannot show where an answer came from.

Each of those has an engineering answer: context that stays the same, interfaces built to the standards, and autonomy set by the people accountable for the work.

Read Gartner’s prediction

What we build

Everything an agent stands on.

Most engagements touch every layer, starting from the bottom.

Context that stays the same

Spiderbrain maps code, records and documents into a scored graph that every agent reads from. Ask the same question twice and the agent receives the same ranked context both times, with the source attached.

  • Spiderbrain
  • MCP server
  • API
  • .spiderbrain format

Interfaces agents can use

We make a business readable and callable by agents: MCP servers over its systems, discovery files, structured data and machine-readable policy, built to the published standards and checked with the tools that score them.

  • MCP
  • Agent cards
  • Schema.org
  • llms.txt
  • Content Signals

Operations agents can run

We redesign intake, scheduling, admissions, triage and filing so agents carry the routine load and people keep the decisions. Every action is logged and every agent can be paused.

  • Autonomy levels
  • Approvals
  • Audit trail
  • Kill switch
Work in the field

Where it is already running.

We keep our clients’ names private. These are the kinds of organisations we have built for, and what changed in how they work.

EducationDelivered

Admissions that answer every applicant

Institutes and colleges use our systems to run their advertising and admissions: campaigns that reach the right applicants, and assistants that answer them in their own language, day and night.

WhatsApp assistantsCampaignsCounselling bookingsFee follow-upRead how it works HealthcareDelivered

Front desks that keep up with every patient

Clinics and health services use our systems to answer, schedule and follow up with patients, and to prepare paperwork for clinicians to review and sign.

Patient intakeSchedulingRemindersDocumentation draftsRead how it works SoftwareDelivered

Codebases every assistant reads the same way

Software teams use Spiderbrain and our agent workflows so coding assistants, support and engineering share one grounded picture of the system.

SpiderbrainCoding agentsSupport triageOnboardingRead how it works GovernmentDelivered

Files that arrive read, summarised and routed

Public offices use our systems to handle citizen requests in every language and to move files with a draft noting attached, while officers decide.

Citizen servicesFile movementPolicy answersGrievancesRead how it works
Governance

You set how far each agent may go.

Autonomy is a setting, chosen per task and per risk. Most systems mix levels: an agent may draft every reply and send only the ones a person approves.

Prepares the work. A person finishes it.

The agent writes the reply, the letter or the noting. Nothing leaves until a person has read it.

For exampleDrafts the file noting that an officer edits and signs.

Every action loggedAutonomy set per taskAny agent can be pausedDeployed in your region

Our platform

Spiderbrain gives every agent the same map.

Spiderbrain turns code, records and documents into a scored, source-free graph and serves it over MCP and an API. Agents query the graph and get ranked, cited context, so what they read does not drift between runs or between tools.

  • DeterministicThe same input builds the same brain, every time.
  • Source-freeA brain holds structure and scores, never your source.
  • Open at the edgesMCP for any agent, an API for your services, an MIT format you can take anywhere.
Explore Spiderbrain spiderbrain.ai
agent session, illustrative
# an agent asks the brain before it answers
call spiderbrain_search
  query: "where is the fee waiver rule?"

→ policy/fees.md § 4.2      score 0.94
→ forms/waiver.json         score 0.81

# same brain, same ranked context, every run
An illustrative agent session: the agent searches the Spiderbrain brain and receives ranked, cited sources.
Open work

Parts of the agentic web anyone can use.

A healthy agent ecosystem needs shared formats and honest measurement. We publish ours, and we test our own platform against them.

.spiderbrain/An open context format

MIT-licensed readers on npm and a listing on the official MCP Registry, so a brain is never locked to one vendor.

See it on npm contextbenchmarkAn open test for context

Measures whether an AI context layer gives the same answer twice. Vendor-neutral, and it tests ours too.

Run the benchmark field notesThe agentic web, in plain words

What changed, which standards matter and what they mean for an ordinary business, with every figure sourced.

Read the field notes
Blog

Reading for people who run agents.

Our blog covers AI agents and the marketing, data and commerce systems they now work inside. These are a good place to start.

AI agents · 11 min readAgentic programming security: the fundamentals most teams skipAgentic programming security in plain terms. The common gaps we find auditing AI-built codebases, and the small fixes (CSP, secret scanning, least privilege) that close most of them.AI agents · 10 min readPrivacy best practices for agentic AI: a consultant's checklistAgentic AI privacy best practices. The data-handling gaps we find auditing AI agents, and the small fixes that keep PII out of prompts, logs, and third-party models.AI agents · 10 min readAI agent governance: the framework most teams build too lateAI agent governance in practice. The governance gaps we find when agents are already in production, and the lightweight framework that fixes them without slowing the team.AI agents · 11 min readAgentic AI compliance: what changes when the agent decidesAgentic AI compliance explained. The EU AI Act, GDPR automated-decision rules, SOC 2 scope, and the compliance gaps we find when an AI agent is in the loop.

AI, agents & LLMsAlgorithms, attribution & analyticsProgrammatic advertising & searchAffiliate & partnership marketingContent creationEcommerce platformsCDP & journey managementTechnical SEOAEO & GEOAgency & implementationAll posts

Careers

Build the agentic web with us.

We hire engineers and partners who think for themselves. Roles are open now, on site in Bengaluru and Delhi and remote around the world.

See all open roles
Questions

What people ask us first.

Short answers. The longer ones are in how we work, the field notes and what an AI agent is.

What does Perform Digital do?

Perform Digital is an AI company, operating since 2019. We build AI agents, the platforms they run on and the context they read from, and we redesign operations such as admissions, patient access, support triage and citizen services so agents carry the routine work while people keep the decisions.

How long has Perform Digital been operating?

Since 2019, which is over seven years. Perform Digital Private Limited was incorporated in India on 3 October 2019 (CIN U72900UP2019PTC121932) and is registered in Prayagraj, Uttar Pradesh. Over that time it has delivered data, marketing technology and AI work, and today it builds AI agents, the Spiderbrain context platform and agent-run operations.

Which industries do you work in?

Education, healthcare, software and government. We have delivered agent-run operations in each of them. We keep our clients’ names private, so the work is described by sector.

What is the agentic web?

The agentic web is the part of the internet where software agents read pages, compare options and complete tasks on a person’s behalf. It runs on open standards such as the Model Context Protocol, Agent2Agent and llms.txt. Our field notes explain each one in plain words.

What is Spiderbrain?

Spiderbrain is our context platform. It maps code, records and documents into a scored graph and serves it over MCP and an API, so every agent reads the same ranked context with its source attached.

How do you keep AI agents under control?

Autonomy is a setting, chosen per task: observe, draft, act with approval, or act within limits. Every action is logged, any agent can be paused, and systems are deployed in the region you choose.

Are you hiring?

Yes. We have open roles in engineering and partnerships, on site in Bengaluru and Delhi and remote. Every role and how to apply is on our careers page.

Start here

Bring us the operation that slows you down.

We will map it with you and say plainly where agents help, where they do not, and what it takes to run them safely.

Contact us