Intelligence
into action.
Divishta builds AI agents that develop, migrate, test and AI-enable the software you already run, on private models and on infrastructure you control. Your data never leaves the pipeline.
One AI workforce for the software you already have.
We don't sell another app. Each agent plugs into your existing code, data and tools, does the work, verifies it, and hands you the evidence.
Development
Specs become tested pull requests in your existing codebase. Senior engineers approve every merge.
Migration
Move databases, ERPs and platforms with row-level reconciliation and an evidence pack you can audit.
Testing
Autonomous QA that explores your app, writes real test code and runs it on every change.
AI Enablement
Private copilots over your documents and website agents that act, wired into your CRM and ERP.
Autonomy with accountability.
Every run follows the same five-stage loop. Agents do the repetitive work at machine speed; people decide anything that's hard to undo.
- 01
Understand
Read the input, whether it's an email, spec, schema, PDF or ticket. Extract what's needed and flag what's missing instead of guessing.
- 02
Plan
Produce an executable plan using only the tools this agent is permitted to use, with a step budget and cost ceiling.
- 03
Execute
Call approved APIs, databases and repos with scoped, revocable credentials. Every action is idempotent and logged.
- 04
Verify
Independent checks: tests, reconciliations, business rules and citations. If it can't be verified, it doesn't ship.
- 05
Report
An evidence pack and audit trail for every run. Uncertain, financial or irreversible decisions go to a human queue.
Your data never leaves the pipeline.
Most "AI solutions" forward your documents to a model you don't control. Ours run on open-weight models hosted on our private servers or inside your own cloud, with no third-party AI in the default path.
No training on your data
Documents are retrieved at question time and never used to train any model.
No prompt logging
Prompts and answers aren't stored by default. Only audit metadata is kept.
Tenant isolation
Permissions are enforced in the retrieval layer, not left to a prompt instruction.
Full audit trail
Every agent action is recorded, with deletion on request.
Big models. Small machines.
Cheap, private AI depends on running capable models on modest hardware. We built our own streaming inference engine in Rust and benchmark everything under hard memory caps. These are measured numbers, not marketing estimates.
Peak RAM to run a 604 MB language model with identical output, using our Squeeze engine on a laptop.
Faster document answers from prompt-lookup speculation. One weight pass verifies several tokens.
Mixture-of-experts model served from disk on a 2-vCPU server with RAM capped far below its 12 GB size.
Start small. Prove value. Then scale.
Fixed-price pilots with a measurable outcome, then a predictable monthly plan. No open-ended consulting meters.
Workflow Audit
We map one workflow, estimate hours saved and tell you honestly whether AI is worth it.
- Process & data map
- ROI estimate
- Risk & privacy review
Fixed-price Pilot
One agent on one real workflow in 2–3 weeks, with success criteria agreed up front.
- Working agent in your stack
- Evidence & accuracy report
- Go / no-go decision
Operate
We host, monitor, improve and extend the agent, with monthly outcome reporting.
- Private hosting or your VPC
- Model updates & evaluations
- Priority support
Straight answers.
Do you send our data to ChatGPT or other AI companies?
No, not by default. Our agents run on open-weight models hosted on our own servers or deployed inside your cloud. A frontier API is only used for a specific task if you approve it in writing.
How autonomous are the agents really?
They complete routine work end to end: reading, planning, executing and verifying. Anything financial, irreversible or uncertain goes to a human approval queue. Autonomy without accountability isn't a product.
Do we have to replace our existing software?
No. That's the point. Agents connect to what you already run, through APIs, databases, repos, a single website script tag, Teams or Slack.
Who owns what you build?
You own the code, scripts, tests and data. Our platform is licensed, but your work product is yours to keep.
Can it run fully on-premise?
Yes. We package the stack in containers that run on your servers, with local models, a local vector database and no mandatory external calls.
Bring us one
painful workflow.
Tell us what slows your team down. You'll get a straight assessment within one working day, even if the answer is "don't use AI for this".