Our GPU, your use case.
We run our own GPU and build generative workflows for one job at a time: catalogue imagery, calls, meetings, research. You get industry-standard quality at a cost that makes sense, without renting AI by the seat.
One workflow, tuned to your business.
Each of these runs in production for a client today. We pick the model, train or tune it on your data, and wire the output into the system your team already uses.
Visual models
Models trained on your real pieces produce catalogue images that keep stones, metal and texture true to the SKU. Replaces per-image photo tools.
Voice agents and call intelligence
Calls in Hindi, Marathi and English answered, transcribed, summarised and logged against the lead, with follow-ups raised automatically.
Meeting and concall summaries
Google Meet, Zoom and earnings calls turned into decisions, numbers and action items the same hour.
Private language models
Self-hosted models for fund memos, client data and contracts, answering from your own documents without sending them to a third party.
Documents to data
Invoices, POs, KYC packs and filings read into structured records, with a person approving anything uncertain.
Agents on WhatsApp
Rate requests, order status and catalogue replies handled on WhatsApp, with every action written back to your CRM.
Inbox triage
Email read, tagged and routed: deals to the pipeline, invoices to finance, replies drafted for approval.
Research report drafts
Equity research first drafts from annual reports and concalls, every figure cited to its source page.
A studio your team runs, on our GPU.
Batch jobs, review queues and model settings in one place, with no per-image or per-seat fee.
Shown with demo data. A counter photo becomes a catalogue image, weight read from the tag, listing copy in three languages, published everywhere.
Private AI that reads for you.
Inboxes, filings and transcripts are where funds and PMS teams lose their hours. These workflows run on models the firm controls, so nothing confidential lands in someone else's SaaS.
Inbox triage for a venture fund
Every pitch, LP note and invoice is read, tagged and routed. Founder emails become pipeline entries with the deck summarised, replies are drafted for a partner to approve, and newsletters stay out of the way.
Part of Roots Ventures' self-hosted AI operating system, which also makes a separate dealflow subscription such as Taghash unnecessary.
Read the Roots Ventures storyEquity research drafts for PMS teams
Annual reports, concall transcripts and five years of financials go in; a structured first draft comes out, with business overview, ratios, peer comparison, valuation and risks, every figure linked to its source page. The analyst edits and signs off.
One owned workflow in place of several premium research and data subscriptions.
See software for PMS firmsPay for outcomes, not seats.
Per-seat AI SaaS charges you more as your team grows. An owned workflow on our GPU costs the same whether five people use it or fifty.
- Bill grows with every user
- Generic model, generic output
- Your data trains their product
- Five tools for five jobs
- Fixed build, then fixed AMC
- Tuned on your samples
- Private by default, zero retention otherwise
- One workflow wired into your system
Running on real calls and real data.
calls logged in Jewel Casa's CRM, each with an AI call summary in Hindi, Marathi or English.
Jewel Casa · jewellery retailCatalogue imagery now comes from a model trained on Jewel Casa's own pieces, replacing Photoroom.
Jewel Casa · cataloguefrom proof of concept to a self-hosted AI operating system for dealflow, research and LP reporting.
Roots Ventures · VC fundBefore you ask.
What teams want to know before moving a workflow off a SaaS tool.
Whose GPU does the work?
Training and heavy generation run on Ekalon's own GPU, so you do not rent cloud GPUs by the hour or pay per image. The workflows, prompts, fine-tuned weights and outputs you commission belong to you.
Does our data leave our control?
Sensitive data stays on private models that run on infrastructure you or we control. Where a frontier model gives clearly better quality, we call it with zero data retention and tell you exactly which fields go out.
Is the quality as good as the paid tools?
That is the brief. We benchmark outputs against the tool you use today on your own samples before anything goes live, and keep a human approval step where it matters.
What if a better model comes out next month?
Models are swappable. The workflow, data and evaluation set stay the same, so we can test the new model on your samples and switch if it wins.
Send us one task you pay an AI tool for.
We will test it on our GPU with your samples and tell you if an owned workflow can match the quality.