Re-entering incoming documents
Turn requests into structured candidates, flag missing fields, and keep approval with the team.
Try the intake example →AI workflow automation & private knowledge systems
AI automation fordocument-heavy operations.
Turn incoming documents into reviewed, structured work—and help your team find answers in approved company knowledge.
Assessments: $1,500–$3,000. Start with a fit discussion; no purchase commitment.
Founder-led from discovery through handoff
Human review for consequential actions
Ownership and handoff defined before build
India-based · remote-first
One bounded workflowIllustrative process
01
Intake
Approved documents, requests, or records
02
Assist
Extract, retrieve, classify, or draft
03
Review
A person approves consequential output
04
Route
Send the approved result to the right system
The assessment decides which steps need AI, which should remain deterministic, and where a human must stay in control.
Where is your team losing time?
Searching across internal knowledge
Help staff find answers in approved sources, with citations and permission boundaries.
Explore private knowledge systems →Unsure what is worth automating
Map the current process, compare options, and define a measurable first pilot.
See a sample assessment →Explore the approach
Try a workflow. Inspect the decisions.
Working demo · synthetic inputs
Human-approved document intake
1. Intake2. Validate3. Review4. Approve
Correct a missing amount, reject a duplicate, and approve a simulated record. See how exception handling changes the outcome.
Try the working example →Illustrative deliverable
A workflow assessment you can inspect
See the workflow map, options, risks, acceptance checks, and pilot decision in a sample report. Download the editable template without sharing an email.
Read the sample assessment →These are synthetic examples. They demonstrate the approach and do not claim client adoption or measured savings.
Start with a paid assessment
Choose the right workflow before committing to a build.
In 5–10 business days, we map one repeated workflow, define its manual baseline, inspect data and integration constraints, and turn the best-fit opportunity into a fixed-scope pilot with clear acceptance criteria.
Planning price: $1,500–$3,000
One workflow. No production build, legal opinion, or compliance certification included.
What you receive
- Current-state workflow and bottleneck map
- Data, integration, privacy, and failure-risk review
- Ranked AI and automation options—including a do-not-automate decision
- Target architecture and human-review points
- Pilot scope, acceptance criteria, timeline, and fixed-price proposal
Two primary implementation paths
Start with the business workflow
Technology is selected after the workflow, source data, review needs, and acceptance criteria are clear.
Founder-led delivery
Work directly with Abhay Rana from assessment through handoff.
AI Systems Studio is an India-based, remote-first practice. Scope, collaboration hours, review cadence, ownership, and support boundaries are agreed before implementation begins.
Delivery principles
Clear scope, grounded answers, clean handoff.
One named workflow owner and one measurable baseline before a pilot
Representative inputs and acceptance criteria before model selection
Human review where an incorrect action could matter
Explicit provider, data-flow, retention, and operating boundaries
Failure paths, logs, fallbacks, and handoff included in scope
No performance or business-outcome claim without a measurement record
A staged path from uncertainty to operation
Larger commitments follow evidence. A pilot does not become “production” until its data, risks, acceptance criteria, ownership, and operating responsibilities are clear.
01
Assess
Map one workflow, its baseline, source systems, users, constraints, and failure cases before choosing tools.
02
Pilot
Prove one bounded use case against agreed acceptance criteria, representative inputs, and review rules.
03
Implement
Extend a valid pilot with the integrations, controls, documentation, deployment, and training the real workflow requires.
04
Optimize
Review failures, evaluation results, operating cost, model changes, and bounded improvements after launch.
Assessment questions
Questions before you scope an AI system
A good first conversation is specific: the workflow, the data, the users, and what the system should be trusted to do.
What kind of AI system should we build first?
Start with one repeated workflow that has a named owner, representative inputs, measurable volume, and a clear reviewable output. The assessment may also conclude that the workflow should stay manual or use standard automation instead of AI.
Can this work with our private company data?
Potentially, but only after the data flow, provider terms, access rules, retention, deletion, and security responsibilities are agreed. Do not send confidential material through the public contact form.
Do you only build chatbots?
No. Chat is only one interface. A project may use retrieval, structured extraction, classification, drafting, deterministic rules, APIs, or human approval depending on the workflow.
Can you connect AI to tools we already use?
Integration feasibility is checked during assessment. Access, API limitations, data sensitivity, failure handling, and ownership determine what belongs in the first pilot.
Will our team own the system after launch?
Ownership, repositories, hosting, credentials, documentation, and support are defined in the proposal and contract before implementation. They are not assumed from a marketing page.
What should we send before a project call?
Send a non-confidential description of the workflow, approximate volume, current tools, user roles, timing, and what an acceptable output should look like. Representative files can be reviewed later through an agreed secure channel.
Know what to automate before you pay to build it.
Bring one repeated workflow, representative inputs, the current tools, and the outcome you need. The paid assessment turns that into a clear decision and a bounded pilot.