95% of enterprise AI pilots stall on deployment rather than on the model, and mid-market stalls hardest. No platform team, no data engineering bench, and no one who owns the last mile.
Bastion is the last mile. The interfaces stay stable while the engines get swapped underneath.
The stack
Spoggle
Understands meaning of data
Patented semantic data clustering. Warehouse-ready models with no pipeline code and no schema design.
Cortex
Live library of everything
Enterprise memory. A self-correcting compiled wiki, not a RAG index.
Almanac
Forecasting & other algorithms tuned for your enterprise
The model library. Four families in production: TailML, SpaceML, PriceML, and ResidualML.
Crucible
Plumbing that directs AI agents
The agent harness. Agents red-teamed against adversarial inputs, failures iterated.
Courier
Clicks and types for you
Agentic RPA. Reads the screen and acts inside the systems you already run.
Lisa
Talks to your customers
The voice layer. More than a million production users across utilities and healthcare.
Brief
Explains what changed, in words
Conversational reports. Cortex and Almanac turned into language an operator reads, with the rows cited.
Assay
Proves it works before launch
The verdict layer. Models scored before they ship, agents red-teamed, drift watched after.
Bastion is not a toolbox. Each layer feeds the next, and every layer ships with named systems we built and own.
Spoggle · Cortex
Scattered enterprise data becomes structured, queryable context. Spoggle auto-discovers the relationships across CRMs, ERPs and SaaS tools and builds warehouse-ready models with no pipeline code. Cortex compiles what the company already knows into a self-correcting wiki that every agent reads from.
Almanac
Almanac is the model library: four families in production. TailML forecasts rare events. SpaceML predicts the impact of confounding variables. PriceML prices commodities and revenue realization. ResidualML underwrites equipment leases from the lessor's own portfolio rather than industry tables. Trained on your data, retrained weekly, validated on live trading desks.
Crucible · Courier
Crucible is the agent harness: agents are red-teamed against adversarial inputs and the failures get iterated. Courier reads the page and decides, filling forms, clicking buttons and submitting transactions inside the systems you already run.
Lisa · Brief
Lisa is the voice layer, live with more than a million production users across utilities and healthcare practices, handling claim status lookups, scheduling and intake. Brief turns Cortex and Almanac into language: weekly operator reports, board-ready summaries, and ad-hoc questions answered from the company's own context rather than a generic model. Ask Brief why margin moved and it cites the rows.
Assay
Assay is the verdict layer. Every model is scored against held-out data before it ships and watched for drift after. Every agent is red-teamed against adversarial inputs and its failure modes are logged rather than patched over. Nothing reaches production on a demo. It reaches production on a number.
Most applied-AI firms automate workflows. We model the economics underneath them.
Inside the five layers sits the engine. Spoggle turns scattered data into agent-ready context. Crucible runs the agents on Cortex's memory and Almanac's predictions. Courier takes the action back out into the world, and Brief writes back what changed in words an operator reads. Assay scores every model and agent before any of it ships, and three loops close the system on itself.
Every action produces new data. Every decision becomes future context. Every outcome retrains Almanac, and nothing ships until Assay says so.
Data orchestration
Patented semantic data clustering. Takes scattered data from CRMs, ERPs, and SaaS tools, auto-discovers the relationships, and builds warehouse-ready data models. No pipeline code, no schema design, no data engineering team. Runs in your own infrastructure.
Six months of data engineering done in days.
Agent harness
A self-improving agent harness built on open-source Hermes. Agents are red-teamed against adversarial inputs; the failures get iterated. Data comes from Spoggle, predictions from models built on Bastion, and decisions flow to Courier to act and Cortex to remember.
Only agents that survive red-teaming reach production.
Organizational memory
Not a RAG system. Cortex is a self-correcting compiled wiki. LLMs read from Slack, Meet, Drive, Git, email, and code, and compile structured markdown via a four-phase cycle: ingest, compile, query, lint. Three internal agents, each with strict permission separation.
Zero behavior change for the team. Cortex reads from the channels they already use.
Agentic RPA
Courier reads the page and decides. When Crucible issues a task, Courier executes each step by understanding what is on the screen in real time. It fills forms, clicks buttons, submits transactions, and returns fresh data to Spoggle.
No pre-recorded workflows. No brittle selectors.
The model library, four families deep. TailML forecasts rare events where the tail is the whole risk. SpaceML reads confounded industrial systems. PriceML prices commodities and revenue realization through an ensemble rather than a single estimator. ResidualML underwrites equipment leases from the lessor's own portfolio. Crucible calls them as predictions; Cortex's accumulated outcomes retrain them.
Reporting layer
Cortex holds what the company knows and Almanac holds what it expects. Brief turns both into a written read-out, scheduled or asked for, in the channel the team already works in. Every claim carries the rows it came from, so a number can be checked rather than trusted.
A dashboard shows the number. Brief tells you why it moved.
The verdict layer. Every model is scored against held-out data before it ships and watched for drift after. Every agent is red-teamed against adversarial inputs and its failure modes are logged rather than patched over. Nothing reaches production on a demo. It reaches production on a number.
Courier's real-world outputs become new data in Spoggle. The system's actions become its next inputs, so every engagement grows its own dataset.
Crucible writes every decision and learning to Cortex. The next agent starts with everything the previous agents knew. Institutional memory without the institutional latency.
Cortex's accumulated outcomes become training signal for Almanac, the model library. Those models get sharper as the system operates. The longer it runs, the better it runs.
Inside Almanac
TailML
Transformer-based models that forecast rare-event scenarios, where the tail is the whole risk. Deployed in: energy price spikes, demand shocks.
SpaceML
State-space models for predicting the impact of confounding variables in systems where everything moves at once. Deployed in: paper mill energy, industrial process control.
PriceML
Price prediction for commodities and revenue realization through an ensemble of models rather than a single estimator. Deployed in: deregulated power markets, pricing intelligence.
ResidualML
Lease-specific depreciation models built from the lessor's own portfolio, not industry tables. Powers underwriting and six-month-ahead portfolio monitoring. Deployed in: Equipment leasing.
Bastion is not self-service. Every deployment comes with the platform, the engineers who built it, and the operator who owns the outcome.
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