The usual way
A 12-month roadmap deck
Beautifully argued, never shipped. The calendar moves; the operation does not.
AI TRANSFORMATION CONSULTING // END-TO-END ENGINEERING
We cross out the hype. We build what works.
TEAM OF 150+ · 10+ YEARS · ISO 9001:2015 · CMMI L5
CERTIFIED EXPERTS MICROSOFT · AWS · GOOGLE · ORACLE · SERVICENOW · SALESFORCE
- Your cloud Deployed inside your AWS, GCP, or Azure account
- Human sign-off A person approves anything consequential
- Evals first Written before the agent, run against your data
- Live in 90 days One workflow to production on a schedule
- Run after launch Monitoring, guardrails, and cost control
- You own it Code, models, and evals land in your repositories
DAY 00 // ENTERPRISE AI STRATEGY
You do not need an AI strategy deck. You need one workflow in production.
The usual way
A platform purchase before the first win
License first, use case later. The tool arrives before anyone knows what it is for.
The usual way
Pilot after pilot
Each demo impresses the room. Monday stays the same.
The usual way
AI everywhere at once
Forty use cases on a slide. None of them owned, none of them live.
The working way
One workflow that matters
Picked in week one, inside your operations, with the requirement in writing.
- Live in your systems in 90 days
- Wired into the ERP, CRM, and queues you already run. Your cloud, your data.
- A number that moves
- One metric, agreed up front, monitored after launch. That is what production means.
- Then the next one
- The second workflow reuses the data work, the evals, and the guardrails of the first.
One becomes two. Two becomes the operation. That is the whole strategy.
DAY 01 // AI TRANSFORMATION CONSULTING
The first five days are already scheduled.
Week one runs inside your operations, not a conference room. Five days, each with a job, ending in writing.
-
MON
Sit with your team
We watch the real work run end to end, as it actually happens. No slide decks.
-
TUE
Map every workflow
Everything the work travels through, on one list, in plain language.
-
WED
Cross most of it out
Workflows that need a rules engine, a template, or a process change get named as exactly that.
-
THU
Pressure-test the one
The survivor shows its data, its metric, and where a person signs off.
-
FRI
Commit, in writing
The requirement, the tool choices, and the 90-day plan for the workflow that earns it.
AN EXAMPLE WEEK. YOURS WILL COUNT DIFFERENTLY.
12 mapped · 11 cut · 1 kept
By Friday you know where AI belongs, and where it does not.
DAYS 01-90 // AI IMPLEMENTATION
90 days. Crawl, walk, run.
Not a roadmap deck. An implementation schedule. One AI workflow goes from idea to production in 90 days: Crawl, Walk, Run. We call it CWR90.
PHASE 01 DAYS 01-30
Crawl
We map your operations and mark where AI belongs, and where it doesn't. You get the requirement, the tool choices, and the plan in writing.
- Use case shortlist, scored D08
- Data readiness audit D15
- Tool selection, with reasons D23
- The plan, in writing D30
PHASE 02 DAYS 31-60
Walk
We build the one workflow that matters. Low stakes, real data, your systems, your people watching it work.
- Working agent in your systems D38
- Evals written before the agent D45
- Human checkpoints designed in D53
- Weekly demos on real data D60
PHASE 03 DAYS 61-90
Run
It goes to production and we run it with you. Monitoring, guardrails, and a number that moves.
- Live in production D68
- Monitoring and guardrails D75
- Cost per run, tracked D83
- The day-91 runbook D90
If day 30 shows AI does not belong where you thought, we say so, and the plan changes. That is the point of crawling first.
Day 01 is a thirty-minute scoping call. Book day 01 →
DAY 90 // AI AGENTS IN PRODUCTION
Shipped. Still running.
Not projections. Engagement records.
Agents in production
Industrial 2025
Agentic AI industrial solutions
Document retrieval: 10 minutes to under 30 seconds
Read the case study
AI lending platform live
Fintech 2025
Accelerating lending with AWS
200+ loan programs, one platform
Read the case study
End-to-end build, live
Healthcare 2023
EHR integration for senior living care
Live across 200+ care sites in 12 states
Read the case study
150+ team members 10+ years shipping software 50+ clients worldwide ISO 9001:2015 · CMMI L5
AND WHEN AI IS ONLY HALF THE JOB
The same bench builds the whole product.
Web, mobile, data, cloud, devices. You do not need a second vendor to finish the job.
UNDER THE HOOD
One accountable bench, not six subcontractors.
One team, one written plan, one owner. The engine's capabilities share the same evals, the same guardrails, and the same delivery discipline, so a decision made in week one propagates through everything that ships.
- 06 Your operations ERP · CRM · queues · floor
- 05 Agent layer Orchestration · integration
- 04 Evals & guardrails Tests · audit · kill switch
- 03 Data layer Readiness · pipelines · lineage
- 02 Model gateway Anthropic · OpenAI · open-weights
- 01 Your cloud AWS · GCP · Azure · your VPC
WHAT WE DO
The capability behind the promise.
Six disciplines, one bench. This is the standing muscle every engagement draws on, whether it is a 90-day agent or a complete platform built end to end.
One
bench
Six disciplines
since 2010
Foundations
Data readiness & engineering
Agents inherit every gap in your data. Schemas, quality, lineage, and access get fixed before anything is built on them.
Schema · Quality · Lineage · Access
Foundations before agents Data engineering
Build
Agentic & applied AI
One workflow that matters, with evals written before the agent and human checkpoints where they count.
Evals · RAG · Document AI · Predictive
Evals before the agent Applied AI
Systems
Agent integration engineering
Wired into the systems you already run, with the access controls your auditors expect.
ERP · CRM · Queues · EHR · MCP
Retrofit-first Applied AI
Operate
AgentOps & managed operations
Production is the starting line. We run what we ship, on a managed retainer.
Monitoring · Evals in prod · Cost control
We run what we ship AgentOps
Govern
Guardrails & human sign-off
Nothing consequential ships without a named person approving it.
Role scope · Audit trail · Kill switch
Every consequential action audited AgentOps
Deliver
End-to-end product engineering
When the workflow needs a product around it, the same bench builds it. Ten years of complete platforms.
Web · Mobile · Data · Cloud · Devices
Ten years of shipped platforms All services
THE LOADOUT
The stack this bench actually works in.
Named, not implied. Every line below has shipped in a client engagement, and the list is reviewed rather than generated.
76 named / 6 domains / reviewed, not generated
- 01 AI & ML 20 models, orchestration, evals, vectors
Anthropic Claude OpenAI Mistral AI DeepSeek Meta Llama Hugging Face LangChain LangGraph LlamaIndex MCP Ollama PyTorch TensorFlow scikit-learn MLflow Jupyter NVIDIA Qdrant Pinecone
- 02 Languages & backends 12 the services behind the agent
Python TypeScript JavaScript Node.js Go Rust FastAPI Django Express Laravel Ruby on Rails WordPress
- 03 Web & product 8 what your users actually touch
React Next.js Astro Vue.js GraphQL Tailwind CSS Vite Figma
- 04 Mobile 5 shipped to both stores
Flutter Dart Kotlin Swift Android
- 05 Data 15 the foundations agents depend on
PostgreSQL MySQL MongoDB Redis Elastic Stack Snowflake Databricks BigQuery Apache Kafka Apache Airflow Apache Spark RabbitMQ Salesforce Oracle SAP
- 06 Cloud & DevOps 16 where it runs and how it stays up
AWS Azure Google Cloud Kubernetes Docker Terraform Ansible NGINX Firebase Supabase Prometheus Grafana Git GitHub GitLab n8n
// Reviewed for accuracy, not for length. If something you depend on is missing, ask: the answer is usually yes, or an honest no.
INTEGRATIONS
Your systems, one expert in the loop.
A HyScaler expert sits between the tools you already run and the surfaces where your teams work: wiring the agents in, and moving governed data both ways. Pick a workflow and follow one request, end to end.
trace/invoice-4471
Finance ops
- SharePoint invoice.received scope · read:documents
- Agent fields.extracted evals passed before release
- Oracle ERP po.matched scope · read:orders
- HyScaler expertise approved named sign-off · nothing consequential moves without it
- Oracle ERP invoice.posted scope · write:invoices
- Audit trail entry.written who approved · what changed · when
trace/case-8823
Customer support
- Salesforce case.created scope · read:cases
- Agent intent.classified evals passed before release
- Retrieval policy.cited sources returned with the answer
- HyScaler expertise approved named sign-off · the reply is a person's call
- Salesforce reply.posted scope · write:cases
- Audit trail entry.written who approved · what changed · when
trace/referral-2190
Healthcare
- EHR · FHIR referral.received scope · read:patients
- Agent codes.suggested evals passed before release
- Redaction pii.masked nothing leaves your tenancy
- Your clinician approved a clinical call is never the agent's to make
- EHR · FHIR record.updated scope · write:encounters
- Audit trail entry.written who approved · what changed · when
trace/order-5567
Supply chain
- SAP exception.flagged scope · read:orders
- Agent cause.diagnosed evals passed before release
- PostgreSQL history.checked scope · read:shipments
- Your ops lead approved the fix named sign-off · nothing consequential moves without it
- SAP order.corrected scope · write:orders
- Audit trail entry.written who approved · what changed · when
trace/incident-3312
IT service desk
- ServiceNow incident.raised scope · read:incidents
- Agent logs.correlated evals passed before release
- Elastic Stack traces.searched scope · read:logs
- Your on-call engineer approved the runbook step a production change is never the agent's to make
- ServiceNow incident.updated scope · write:incidents
- Audit trail entry.written who approved · what changed · when
trace/metric-0914
Data & reporting
- Apache Kafka event.consumed scope · read:streams
- Agent anomaly.flagged evals passed before release
- Snowflake history.queried scope · read:marts
- Your data lead approved the restatement figures are not republished on an agent's word
- Dashboards & BI figures.republished scope · write:dashboards
- Audit trail entry.written who approved · what changed · when
Illustrative traces · every write-back lands in the log
Systems we read and write
Salesforce · ServiceNow · Oracle ERP · SAP · SharePoint · EHR · FHIR · PostgreSQL · MySQL · MongoDB · Snowflake · Databricks · BigQuery · Apache Kafka · Elastic Stack
Surfaces work lands in
Ticket queues · Approval flows · Dashboards & BI · Email & documents · Chat & alerts · Audit reports · Mobile apps · Webhooks & APIs
APPENDIX // REFERENCE
A1 // QUESTIONS
Before you book the call.
The questions engineers get asked in the first thirty minutes, answered up front.
What does a typical engagement look like?
Ninety days in three phases: Crawl (scoping, data and cloud foundations), Walk (the agent or product built and integrated into your systems), and Run (it goes live and we operate it with you). Fixed scope, weekly demos against real data, and written success criteria you sign before we build.
What if AI is the wrong answer for our problem?
Then we say so, in writing, before you spend. Some problems are better solved with a workflow change or conventional software. Shipping the wrong thing helps nobody, and our engineers would rather keep your trust than your retainer.
Do you work inside our existing systems or replace them?
Retrofit-first. Agents are integrated into the ERP, CRM, and ticket queues you already run, with the access controls your auditors expect. A decade of integration work across Microsoft, AWS, Google, Oracle, ServiceNow, and Salesforce is exactly the muscle we use.
How is CWR90 priced?
Fixed price, quoted at the scoping call once we have seen the use case and the systems involved. Delivery runs from Bhubaneswar with a Santa Clara presence, which is why the number does not look like a strategy firm's.
Who owns what we build?
You do. Code, models, prompts, and evaluation suites are delivered into your cloud and your repositories. If we ever part ways, everything keeps running without us.
Do you only do AI work?
No. We have built products and platforms end to end for ten years: web, mobile, data, cloud, devices. The AI work sits on that foundation, and the same bench builds whatever surrounds the agent, so you do not need a second vendor to finish the job.
How do you handle our data?
It stays in your cloud, inside your AWS, GCP, or Azure account, behind your access controls. Nothing is used to train anything outside your walls, and every consequential action an agent takes carries a human sign-off. ISO 9001:2015 discipline covers the process, and ISO/IEC 27001:2022 covers information security.
What happens after the 90 days?
Two honest options. We run it with you on a managed retainer: monitoring, evals, cost control, and improvements month over month. Or we hand it over completely; the documentation, evals, and runbooks are written so your team can operate it without us.
How much of our team's time does this take?
One point person, and a few hours a week from the people who do the actual work, mostly in the first thirty days while we map workflows and sit in on operations. After that it drops to phase-gate reviews and sign-offs. We do the building.
We already ran a pilot elsewhere. Can you pick it up?
Yes, and we will be straight about what we find. We put the existing pilot through evals against your real data, keep what earns its place, and write down what does not and why. Sometimes the fastest path to production starts from what you already paid for.
A2 // FROM OUR ENGINEERS
From our engineers, not our marketing team.
Your day 01
Everything starts with thirty minutes.
Day 01 is a scoping call with an engineer, not a salesperson. Bring the workflow that hurts. If AI does not belong there, you will hear that too.
MIN 00
You describe the workflow, in your words.
MIN 10
An engineer maps what a fix would touch.
MIN 25
You get the straight answer, AI or not.
Prefer email? sales@hyscaler.com