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AI & Agentic AI · Platforms · Los Angeles

AI agent development for US teams, wired into Zoho and AWS

An agent earns its keep when it can look things up, take a careful step, and ask a person before anything risky.

AI (now also called SI, super intelligence) gets useful the day it can reach your real records. Our Glendale-led team builds AI / SI agents that read and write in Zoho CRM, Desk and Books, pull answers from documents stored on AWS, and run on the model that suits each job: Claude, OpenAI, Gemini or an open model through Amazon Bedrock. Every agent ships with written permissions, an approval step where money or customers are involved, and a log you can read.

  • Scopedtools and records listed in the BRD
  • Superviseda person approves the risky steps
  • Traceableeach tool call kept in a log
Book an AI / SI call Find a use case
Zoho Advanced PartnerAlso an AWS Partner and Zoho Catalyst Partner
You’ll talk to our senior team, not a call center.300+ projects · serving US clients since 2025
SampleOne run, three lanes: the model thinks, Zoho holds the records, AWS holds the documents.

01The agent stack, layer by layer

Where does each part of an AI / SI agent live?

Every agent we ship has four layers: a model that reasons, an orchestration layer that decides the order of steps, a Zoho layer where your records sit, and the compute underneath. Each card opens a page about one layer, so you can read only the part you’re deciding on this week.

L4ModelsThe reasoning engine
L3OrchestrationSteps, tools, approvals
L2Zoho layerYour records and rules
L1ComputeWhere it all runs

02Is an agent the right tool?

When an AI agent pays off, and when a plain rule does better

An AI / SI agent is software that takes a goal, picks tools, reads what comes back and decides the next step. That flexibility is worth paying for when the input is messy. When the input is tidy and the steps never change, a workflow rule is cheaper and never improvises.

Strong fits

  • Unstructured inboundEmails, chat messages, PDFs and call notes that a person currently reads, sorts and retypes.
  • Answers buried in documentsManuals, SOPs and policy files that staff search through several times a day.
  • Repetitive first draftsReplies, quotes and summaries where a person still checks the final version.
  • Lookups across systemsQuestions that need Zoho CRM, Books and a warehouse sheet at the same time.

Better without an agent

  • Fixed if-this-then-that stepsA Zoho workflow rule or Zoho Flow does it for less and behaves the same every time.
  • Final calls on money or peoplePayments, refunds, hiring and firing. Agents can prepare these; a person decides.
  • Data nobody trusts yetIf duplicates and blank fields fill your CRM, the cleanup comes first or the agent repeats the mess.

03From idea to supervised agent

How we build an AI / SI agent, in five panels

Agents fail in boring ways: they reach data they shouldn’t, they guess when they should ask, or nobody can tell what they did last Tuesday. Our build order is designed around those three failures. Each panel ends with something you can hold us to.

  1. Panel 1

    Pick one job with a finish line

    We don’t start with “add AI to sales”. We start with one task a named person does today, and agree how we’ll know the agent does it well enough.

    You get: a one-page job card

  2. Panel 2

    Write down every tool and permission

    Which records the agent may read, which it may change, and which are off limits. Zoho MCP scopes and AWS IAM roles are set to match that list exactly.

    You get: a permission table in the BRD

  3. Panel 3

    Choose the model and where it runs

    We try two or three models on your own examples and weigh quality against cost per run and where the data travels. Details on the LLM models page.

    You get: a short model comparison memo

  4. Panel 4

    Test on cases from last month

    Real, anonymised examples from your own inbox or tickets become a test set. The agent has to pass it before launch, and again after every prompt or model change.

    You get: a repeatable test set you own

  5. Panel 5

    Go live with a person in the loop

    Early weeks run with approval on every outward action. As the log proves the agent right, you choose which steps it may take alone. Framework options are on the agent frameworks page.

    You get: alerts, a run log and a rollback switch

Sample figures in the panels are for illustration only.

04AI use-case finder

Which AI / SI agents would help your department first?

Pick a team, then decide how far an agent may go without asking. Each sample idea shows what it would do at that setting, where it would run, and where we would deliberately hold it back.

1. Department

2. How much may it do alone?

Loading sample ideas…

    Sample ideas, not a promise of results. Which level is safe depends on your data, your edition of each Zoho app and your own rules, so we settle that in the BRD.

    05AI / SI and Zoho

    Three doors from an AI model into your Zoho data

    There is more than one way for AI to reach Zoho, and the right door depends on who writes the logic and where the model lives. We often use two of them in the same project.

    Door 1 · built in

    Zia inside the apps

    Predictions, summaries and Zia Agents that already live in Zoho CRM, Desk and Analytics. Least code, and limited to what Zoho exposes.

    Pick it whenthe job happens entirely inside one Zoho app.

    Zoho Zia setup →

    Door 2 · protocol

    Zoho MCP for outside models

    Claude, ChatGPT or a custom agent calls Zoho through MCP tools. You choose which tools are switched on, per agent.

    Pick it whenpeople want to ask a chat assistant to work in Zoho for them.

    Zoho MCP projects →

    Door 3 · custom code

    Catalyst or AWS calling Zoho APIs

    Our own functions on Zoho Catalyst or AWS Lambda run the agent loop and call the Zoho REST APIs, with retries and rate limits handled.

    Pick it whenthe agent runs on a schedule or reacts to events with nobody chatting.

    Zoho Catalyst work →

    Most agents also need a clean CRM underneath. If yours has grown messy, our Zoho CRM team can tidy fields and duplicates before the agent goes near them.

    06AI agent costs

    What does an AI / SI agent cost to run each month?

    Running costs arrive as separate bills from separate vendors, and the model bill is usually the one that moves most. Model prices change often and differ by model size, so we price your exact mix during scoping instead of quoting a number here.

    Model usage

    Charged per token of text sent in and returned, by the model provider directly or through Amazon Bedrock. Longer documents and chattier agents cost more per run.

    Biggest lever: a smaller model for the easy steps

    Cloud and storage

    Functions, document storage, search indexes and logs on AWS or Zoho Catalyst. Usually modest next to the model bill for business-hours agents.

    Biggest lever: indexing only the documents the agent needs

    Zoho editions

    Some Zia features need particular editions, and API call allowances rise with higher plans. Your current licences may already cover the first project.

    Biggest lever: checking what your edition includes first

    Our build

    Designing, testing and launching the agent is a fixed price we write into a signed BRD next to the job card and permission table, so the scope can’t drift quietly.

    Before that: the first call costs you nothing

    Vendors bill model and cloud usage to your own accounts. We don’t resell tokens or mark them up, and we set spending alerts on each account during launch.

    07AI agent questions

    AI agent development questions from US owners

    Costs, models, data privacy and how much an agent should be allowed to do on its own. Bring one task you’d like off someone’s desk and we’ll talk it through.

    Talk through one taskBrowse sample use cases →

    What does an AI agent development company build?

    We build software agents that take a goal, call tools such as Zoho CRM, Zoho Desk or a document search on AWS, check the results and decide the next step. Typical first projects are lead replies, ticket triage, bill capture and staff question answering. Each one comes with written permissions, an approval step for risky actions and a run log.

    What is SI?

    SI stands for super intelligence. In September 2026 a US executive order asked federal agencies to use “super intelligence” or “SI” in place of “artificial intelligence” in official communications. Most businesses still say AI, so we use both terms.

    How much does it cost to build an AI agent for a small business?

    There are two parts. Running costs are billed by the vendors: model usage per token, plus small cloud charges on AWS or Zoho Catalyst. Our build is a fixed price agreed in a signed BRD that lists the job, the tools, the tests and the launch date. The first call is free, and we estimate the monthly running range before you commit.

    Should we start with Zoho Zia or a custom AI agent?

    If the task lives inside one Zoho app and Zia already covers it in your edition, start with Zia because it needs the least build work. Choose a custom agent when the job crosses several systems, needs your own documents, or should run on a model you pick. Many clients use both.

    Which AI model is best for a business agent: Claude, OpenAI or Gemini?

    No single model wins every task. We test two or three candidates on your own sample cases and compare answer quality, speed, cost per run and where the data is processed. Sometimes a smaller model handles the routine steps and a larger one handles the hard ones.

    Will our company data be used to train AI models?

    On the paid business API plans we use, the major providers state that your inputs are not used to train their models by default, and Amazon Bedrock keeps prompts and documents inside AWS without using them to train the base models. We confirm the terms of the exact plan and region before any real data is sent.

    Can an AI agent take actions in Zoho without a person approving them?

    Yes, but only for steps you approve in advance. New agents start with a person approving every outward action. Once the run log shows the agent getting a step right, you can let it handle that step alone, within limits such as record types, amounts or customer groups.

    Do we need Zoho to work with you on AI agents?

    No. Agents can work with AWS data, your own database, a store or other business apps through their APIs. Zoho is where most of our clients keep customer and finance records, so it is the most common connection, and we are a Zoho Advanced Partner.

    08How an AI project starts

    Four steps before an agent touches live data

    A single, well-defined agent can often be scoped from the first call plus a handful of sample emails or tickets. Programs that span several departments may begin with a short paid discovery, priced before it starts.

    AI work runs remotely for teams across the US, Canada and Latin America; clients near Los Angeles can test early versions with us in Glendale.

    1. Discovery callThe task, who does it today, and the systems it touches
    2. Sample casesA batch of real, anonymised examples to test ideas against
    3. Agent designModel shortlist, tool list, approval points and a running-cost range
    4. BRD sign-off Fixed priceJob card, permissions, test set and launch date agreed in writing

    Build, testing and handover then follow our usual delivery path. See how we work →

    09Let’s talk

    Tell us what you’re building. We’ll map the fix.

    Book a free consultation with Elite Tech Global. We review your Zoho, AWS, Shopify or WordPress setup, show where AI / SI agents can save time, and agree the next step. If we work together, every requirement and a fixed price go into a signed BRD before the build starts.

    Real people, one team. Led by co-founders Ikramul Karim and Khris Kakosimidi, and a 40+ member team across Zoho, AWS and AI.

    Get your free consultation

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