Data & AI platform
Automation that survives
contact with production
Atmora's automation platform runs language-model agents, document extraction and deterministic rules against the systems you already own. Every run stores its prompts, tool calls and outputs, so a failure is debugged rather than guessed at.
- Cloud
- Private cloud
- On-premise
- Hybrid
Overview
Agents, document extraction and process mining under one control plane.
Most enterprise automation stalls at the same place: a pilot that reads data well but is never trusted to write it back. The platform is built around that problem. Agents call typed tools with declared side effects, writes carry idempotency keys, and anything the model is unsure about lands in a human review queue instead of quietly entering a system of record. Process mining sits in front of the whole thing so you automate the step that actually costs money rather than the one that was easiest to demo.
It runs on your infrastructure or ours, routes work across hosted and self-hosted models through a single gateway, and keeps a replayable record of every execution. This is not a chatbot builder and it is not a general-purpose orchestration engine. If your process is stable, high volume and fully structured, a scheduled SQL job or a scripted integration will be cheaper to run and easier to certify than an agent.
- 11 minutes down to 90 seconds per document
- Supplier invoice handling
- 72% of documents clear with no human touch
- Straight-through processing
- 38% lower after gateway routing and cache reuse
- Inference spend
- 6 weeks from kick-off, including review workflow
- First agent in production
Modules
What ships in the box
- Process Miner
- Agent Studio
- Document Intelligence
- Human Review Queue
- Model Gateway
- Run Observability
Integrates with
- SAP S/4HANA
- Salesforce
- ServiceNow
- Microsoft 365
- Snowflake
- Databricks
- Okta
- Slack
Capabilities
What it does
Process discovery from event logs
Ingest event logs from your ERP or ticketing system and get the real process graph, including the rework loops nobody documented and the median wait at each step.
Agent Studio with typed tools
Agents call typed tools with declared inputs, outputs and side effects. A tool that writes to a system of record must say so, and the runtime enforces the declaration.
Document extraction with confidence gates
Extract fields from invoices, bills of lading and claim forms. Anything below your confidence threshold routes to a reviewer instead of being written to the ledger silently.
Human review queue
Reviewers see the source document, the extracted field and the model's alternatives side by side. Corrections are captured as labelled data for the next evaluation run.
Model gateway with budget controls
Route by task across hosted and self-hosted models, with per-team token budgets, prompt cache reuse and automatic failover when a provider starts returning errors.
Run replay and audit trail
Every run keeps its prompts, tool calls, retrieved passages and outputs. Replay a stored run against a new prompt version and diff the result before you promote it.
Evaluation harness
Regression suites run on every prompt or model change, scored against a held-out set your own domain experts labelled. Promotion is blocked when accuracy falls past the threshold.
Connectors that write back
Read-only pilots stall. Connectors for SAP, Salesforce and ServiceNow post transactions with idempotency keys, so a retried run cannot create a duplicate record.
Built for
Where this is deployed
Industry
Banking & Financial Services
Payment rails, risk engines and core-adjacent systems built by people who have run them at 03:00 on a settlement night.
Industry
Healthcare & Life Sciences
Clinical and regulated software built to pass an audit, not just a demo.
Industry
Logistics & Supply Chain
Visibility, customs filing and cost-to-serve systems for operators who move real freight.
Industry
Telecom & Media
OSS, BSS and delivery platforms that keep working after launch night.
Industry
Public Sector
Digital services that work for everyone who has to use them, including on a five-year-old phone.
Industry
Manufacturing
Getting the plant floor and the ERP to agree on what actually happened during the shift.
FAQ
Questions we get asked
- Do our documents or prompts get used to train models?
No. Inference runs against providers you nominate under your own contracts, or against open-weights models hosted inside your network. The gateway records what was sent and where, and you can restrict a workspace to self-hosted models only.
- What happens when the model gets something wrong?
Extractions below your confidence threshold never reach a system of record; they queue for review. For agent runs, every tool call is stored with its inputs, so you can replay the run, see the decision point and correct the prompt or the tool rather than argue about what happened.
- How is this different from an RPA tool?
RPA drives a user interface and breaks when the screen changes. This calls documented APIs with typed contracts and handles unstructured input, which is where RPA needs a human. For screen-scraping legacy systems with no API, RPA is still the better tool and the two coexist.