Talk to us

AI workflow discovery + execution

AI use is up. Enterprise impact isn't.

Most teams have licenses, pilots, and coding agents. What's missing is a way to choose the right work and show what changed. Imeritas finds the first workflow, puts it into operation, measures the result, and keeps what works.

Talk to us Explore the Agent Framework

One document-review workflow cut peak review staffing by a reported 63%. Human review stayed for exceptions and corrections. Read the case

Imeritas route switch

Start where you are

You don't need a use case.

Some teams need the first workflow found. Some have a use case to prove. Some have a pilot that needs production controls.

Discovery ends with a plan you can act on. The Value Sprint ends with a workflow that's running and measured.

Reported operating impact

63% less review staffing at peak. Human review stayed.

A processing operation reviews large batches of cases in recurring cycles. Every case has its own start and end dates, and every supporting document has to be checked against that window. Because the window changes with each case, manual review was inconsistent and error-prone.

Workflow

  1. Take in the case and its documents.
  2. Identify each document and extract the fields.
  3. Read the case's start and end dates.
  4. Check every document date against that window.
  5. Check completeness and consistency across documents.
  6. Send exceptions and uncertain results to a reviewer.

Reported result

  • Peak review staffing fell by a reported 63%.
  • Reviewers worked the exceptions instead of checking every field.
  • Human review stayed wherever judgment or correction was needed.
See all three workflows

The same pattern shows up wherever teams check variable document packages against case-specific rules:

  • Customer onboarding
  • Claims packages
  • Loan files
  • Vendor qualification
  • Employee records
  • Compliance submissions
  • Benefits administration

Imeritas Agent Framework

Models will change. The workflow you proved shouldn't have to.

Imeritas keeps the workflow separate from the model underneath it. Choose the right model for each task, route work across providers, and switch providers without rebuilding the process.

The Agent Framework coordinates the context, tools, system access, human decisions, controls, cost, and evidence around each workflow in one reusable execution layer.

Control shouldn't be buried in code. Business administrators decide which roles can use which capabilities, redact defined data classes from supported structured results, and set usage ceilings by task, model, or tool. Denials, redactions, and budget decisions are recorded for audit.

Explore the Agent Framework

The model isn't the hard part. Everything around it is.

Prove before you scale

Prove one workflow. Build from what works.

The first commitment is one measurable result, not an enterprise AI program.

Each proven workflow can make the next one faster and cheaper to build. See how we work

Home/Where to start

Where to start

You don't need a use case.

Some teams need the first workflow found. Some have a use case to prove. Some have a pilot that needs production controls. Pick the one that sounds like you.

Discovery ends with a plan you can act on. The Value Sprint ends with a workflow that's running and measured.

Find the work

Someone reads it, decides what it means, then enters it somewhere else. Start there.

That pattern is where language models do their most useful work today.

CapabilityWhat the model can speed upCommon examples
ExtractTurn documents, images, and free text into structured factsContract terms, product specifications, invoice fields, dates, requirements
CompareCheck information across documents, systems, or versionsAmendments, onboarding packages, pay stubs, policy versions, changing product data
ValidateTest completeness and consistency against defined criteriaRequired documents, mandatory fields, catalog standards, compliance packages
ClassifySort incoming work and identify the next pathService tickets, opportunity types, product categories, exceptions, risk levels
SynthesizeCombine dispersed evidence into a usable decision briefBid requirements, contract review, customer file, product-content brief
DraftProduce a first version grounded in approved factsClarification questions, product descriptions, review notes, response drafts
BuildTurn defined requirements into working software or structured automationCode changes, tests, integrations, configurations, reports, workflow automation

These capabilities show up inside five shapes of work: intake, validation, coordination, knowledge, and execution. Valuable workflows usually combine several.

Why business work is harder

Code arrives with its checks. Business work doesn't.

Many teams found measurable AI value in coding agents first, because the output can be reviewed, tested, and versioned. The harder problem is bringing that discipline to work whose outputs and decisions are harder to check.

A code change arrives with its checks

  • Compared with the original
  • Checked against ticket acceptance criteria
  • Compiled, tested, and scanned
  • Reviewed by a person
  • Versioned and approved before deployment
  • Monitored after release, and rolled back if necessary

Repository permissions, test gates, approval rules, execution logs, and model-cost records make the work and its controls observable.

Most business workflows don't. So we define them as part of the workflow:

  • The evidence
  • The human decision points
  • The controls

Authoritative systems, deterministic validation, and accountable people stay responsible for authentication, consequential decisions, and material ambiguity.

Home/Where to start/Workflow Discovery

Workflow Discovery · 2 to 3 weeks

Find the first workflow worth proving.

Sponsored by an executive, centered on one business unit. It ends with a decision: which workflow to prove first, why it's the right place to start, and what evidence would justify the next investment.

Talk to us

Who's involved

A sponsor, one business unit, and a small operating group.

You don't need to arrive with a use case. The sponsor brings the mandate. The business unit brings the operating context.

The executive sponsor

Defines the mandate and the economic expectations.

The business unit

One owner and a small operating group give access to the work, representative inputs, and how it performs today.

What happens

Three to five candidates, compared on the same terms.

What we do

  1. Ground the work in the unit's objectives, pressures, and economics.
  2. Find where work is slow, manual, fragmented, inconsistent, or hard to scale.
  3. Map three to five candidate workflows in enough depth to compare them.
  4. Assess value, feasibility, risk, readiness, and time to proof.
  5. Select the strongest starting point and write its outcome hypothesis.
  6. Write a bounded proof plan: baseline, participants, controls, costs, and success measures.

What leadership gets

  • A map of the unit's opportunities
  • A prioritized shortlist of workflows
  • A call on each candidate: start, prepare, defer, or stop
  • The operating and economic case for the recommended workflow
  • A proof plan, and an update ready for the next operating or board review

The decision it supports

Which workflow should we test first, why is it the right starting point, and what evidence would justify further investment?

Once the decision is made, a Value Sprint runs the bounded proof and recommends whether to scale, revise, or stop.

Home/Where to start/Value Sprint

Value Sprint

Prove the result on real work.

Set the baseline, redesign the work, and run a bounded proof. Then scale it, revise it, or stop. The Value Sprint ends with a workflow that's running and measured.

Talk to us

How it runs

One workflow. One measurable result.

The first commitment is one measurable result, not an enterprise AI program.

What you get

Evidence you can take to the next investment decision.

At the end of the sprint

  • A redesigned workflow, in operation
  • The result measured against the baseline
  • What it costs to run, and the corrections people made
  • How and where it failed, stated plainly
  • A recommendation: scale it, revise it, or stop

What stays with you

  • Approved knowledge and business rules
  • Integrations with the systems the work touches
  • Controls and exception paths
  • The measures, so the next review uses the same yardstick

Where it starts

From Discovery, or from your own use case.

After Workflow Discovery

The proof plan is already written: baseline, participants, controls, costs, and success measures.

With a use case or pilot

We start by setting the baseline and writing the outcome model, so the proof has something to be measured against.

Home/How we work

How we work

One method, from the mandate to a result you can measure.

Imeritas starts with the result the business needs. The technology decision follows the diagnosis and the evidence it will take to prove impact.

The five stages
StageThe questionWhat you get
1

Ground

What has to change, why now, and who owns the result?A sponsor, an objective, the metric that matters, and a first estimate of what the change is worth
2

Diagnose

Which workflow is holding that result back?The workflow as it runs today, its baseline, where it slows, and where it breaks
3

Design

Where can models, software, and people do the work better?The change, who decides what, the controls, the target, and how it will be measured
4

Prove

Did the redesigned workflow move the result?A bounded implementation, the evidence, the cost, the corrections, and how it failed
5

Scale

What should be reused, expanded, changed, or stopped?A scale decision, reusable parts, controls, and the next workflow

One mandate

Different executives, different questions.

Leadership can agree on doing more with AI and still ask different questions about what "more" means.

ExecutiveThe question behind the mandate
CEO or operating partnerAre we moving fast enough, and where can AI materially improve company performance?
CFOWhat value will this create, what will it cost, and what financial or operating exposure are we accepting?
COOWhich workflows should change, who owns them, and how will service, capacity, or quality improve?
CTO or CIOHow will this integrate with our environment, protect data, remain governable, and scale without creating another fragmented stack?
Business-unit ownerWhere should my team begin, what will change in the work, and how will we know it helped?

These questions are connected. A useful AI initiative needs one business outcome, an accountable owner, a workable way to run it, the right controls, and evidence leadership can use.

Home/In practice

In practice

Three workflows. What changed in each.

Each one takes work people did by hand and turns it into structured evidence a person reviews. Results are as reported by the people running the work, and we say where a figure is an estimate or a model.

Case 1 of 3Document validation

63% less review staffing at peak. Human review stayed.

An operation that has to absorb large seasonal volumes turned repetitive document review into structured exception handling.

The operation reviews large batches of cases in recurring cycles, twice a year. Every case has its own start and end dates, and every supporting document has to be checked against that window. Because the window changes with each case, manual review was inconsistent and error-prone, and staffing had to rise with volume.

The workflow

  1. Take in the case and its documents.
  2. Identify each document and extract the dates and fields.
  3. Read the case's start and end dates from the case record.
  4. Check every document against that case-specific window.
  5. Run the remaining completeness and consistency checks.
  6. Flag anything missing, conflicting, expired, or unusual.
  7. Send exceptions to a reviewer to resolve.

Reported result

  • Peak review staffing fell by a reported 63%.
  • Review labor cost during the peak fell by about 60%, as reported.
  • The operation absorbs seasonal volume without adding reviewers in step with case count.

What stayed with people

  • Exceptions and uncertain results go to a reviewer.
  • Human review stays wherever judgment or correction is needed.
  • The workflow speeds up document review. It doesn't authenticate documents or make the final determination.

Reported operating results. Staffing and labor cost are separate results. Neither is a net return on the whole program.

Case 2 of 3Opportunity identification

The response window starts before anyone has seen the opportunity.

For a company that pursues public-sector contracts, every day spent finding an opportunity is a day taken from deciding whether and how to pursue it.

Across 71,780 active public contract notices with both a posted date and a response deadline

13 daysmedian time from posting to response deadline
23.2%close in under seven days
52.2%close in under fourteen days

Why it matters

For 59,950 biddable notices with both dates, a weekly first look plus a ten-day drafting cycle leaves only 35.3% actionable. Discovery lag can remove an opportunity before the pursuit team has made a decision.

The workflow

  1. Monitor the complete daily opportunity file.
  2. Use the reliable fields for hard filters.
  3. Use the sparse fields for ranking, not exclusion.
  4. Surface relevant work quickly enough for the company to act.

Complete profile of the active SAM.gov opportunity file, September 16, 2026. The 35.3% figure is a timing-model result, not a measured product outcome.

Case 3 of 3Opportunity decomposition

From 3 to 4 hours to about an hour.

We measure against the AI-assisted process capture experts already trust, not the manual one. Nearly everyone in the field already uses a language model somewhere, so the manual comparison would overstate the gain.

ApproachPractitioner-reported turnaround per opportunity
Fully manual, for reference1 to 2 days. No longer the comparison.
Practitioner's AI-assisted process3 to 4 hours to a result the practitioner trusts. This is the baseline.
Imeritas workflowAbout 40 to 60 minutes in total, including human review and correction, with $1 to $3 in model cost. Across about 20 opportunities to date, it has stayed in the same range.

Quality and control

  • The agent has typically found an estimated 96 to 99% of requirements, measured against the reviewer's final corrected list.
  • Every requirement the agent states is checked mechanically against the source documents for supporting language.
  • A reviewer checks for omissions, corrects classification and interpretation, resolves conflicts, and confirms consequential requirements.
  • Reviewers report the results are more complete than the earlier human-only process.

What changes

  • More of the response window is left for pursuit strategy and proposal development.
  • Teams can evaluate more opportunities without lowering the standard of review.
  • Capture and proposal people spend their time on decisions, strategy, and credible pursuits.
  • The structured requirements become reusable context for qualification, capture, compliance, and proposal assurance.

Practitioner-reported early operating observations, not a completed controlled evaluation. Coverage is the reviewer's estimate.

The common thread

Variable inputs, checked against case-specific rules, with a person on the exceptions.

The same pattern shows up in:

  • Customer onboarding
  • Claims packages
  • Loan files
  • Vendor qualification
  • Employee records
  • Compliance submissions
  • Benefits administration
  • Bid and proposal work

Home/Agent Framework

Imeritas Agent Framework

Models will change. The workflow you proved shouldn't have to.

Imeritas keeps the workflow separate from the model underneath it. Choose the right model for each task, route work across providers, and switch providers without rebuilding the process.

Talk to usSee it in practice

The execution layer

The foundation beneath each production workflow.

Imeritas sits as a neutral orchestration layer above any cloud runtime. You keep your systems, your expert methods, and your model choices.

LayerWhat it provides
Workflow orchestrationMulti-step processes, state, routing, exception handling, and completion criteria
Knowledge and contextApproved source material, structured business facts, decision criteria, and reusable knowledge
Models, tools, and systemsThe right model for each task, enterprise applications, data sources, APIs, and partner capabilities, with switching across providers
Human decisionsReview points, approvals, holds, rejections, escalations, and clear ownership
Governance and controlRole-based capabilities, data rules, budgets, usage limits, and tenant boundaries
Observability and evidenceRun history, model and tool usage, cost, decisions, outcomes, and audit records

Many ways into the work

A user request, an incoming document, a system event, a scheduled process, or an API call can start a governed workflow.

Why it matters

The workflow stays tied to its business objective while models, tools, and processes change. Every run follows the same path from model output to approved action, recorded evidence, and a measured result.

Governance

Control shouldn't be buried in code.

Business administrators decide which roles can use which capabilities, redact defined data classes from supported structured results, and set usage ceilings by task, tenant, model, or tool.

Denials, redactions, and budget decisions are recorded for audit.

Limits, stated plainly

  • Redaction covers supported structured results. It doesn't cover free text, results produced before a rule existed, row counts, or tool-call payloads.
  • Human approval steps are built in. Role-based approval routing is built per workflow today, not a standard feature.

The model isn't the hard part. Everything around it is.

Home/About

About Imeritas

The model isn't the hard part. Everything around it is.

Imeritas helps leadership teams choose the AI work worth doing, put it into operation, measure what changed, and keep what works.

What we are

A method and an execution layer.

The method

Ground, Diagnose, Design, Prove, and Scale. It starts with the operating result and ends with evidence leadership can use. How we work

The Agent Framework

A neutral orchestration layer above any cloud runtime. Model choice stays with you. The Agent Framework

How we work with you

What you can hold us to.

  • We start from an operating result, not a technology.
  • We say what was reported, and who reported it.
  • We keep people on the decisions that carry consequences.
  • We name the limits before you find them.
  • We prove one workflow before we ask for a bigger commitment.

Home/Contact

Contact

What result are you trying to improve?

You don't need a finished use case. Bring the mandate, the pressure, or the workflow that isn't working. We'll help you find where to start, what should change, and what evidence would earn the next investment.

We reply to the address you give us.